Bioinformatics

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Gene-Set Analysis is Severely Biased When Applied to Genome-wide Methylation Data.

Publication Date: 2013 Jun 3 PMID: 23732277
Authors: Geeleher, P. - Hartnett, L. - Egan, L. J. - Golden, A. - Raja Ali, R. A. - Seoighe, C.
Journal: Bioinformatics

MOTIVATION: DNA methylation is an epigenetic mark that can stably repress gene expression. Because of its biological and clinical significance, several methods have been developed to compare genome-wide patterns of methylation between groups of samples. The application of gene set analysis to identify relevant groups of genes that are enriched for differentially methylated genes is often a major component of the analysis of these data. This can be used for example to identify processes or pathways that are perturbed in disease development. We show that gene set analysis, as it is typically applied to genome-wide methylation assays, is severely biased as a result of differences in the numbers of CpG sites associated with different classes of genes and gene promoters. RESULTS: We demonstrate this bias using published data from a study of differential CpG Island methylation in lung cancer and a data set we generated to study methylation changes in patients with long-standing ulcerative colitis. We show that several of the gene sets that appear enriched would also be identified with randomized data. We suggest two existing approaches which can be adapted to correct the bias. Accounting for the bias in the lung cancer and ulcerative colitis data sets provides novel biological insights into the role of methylation in cancer development and chronic inflammation respectively. Our results have significant implications for many prior genome-wide methylation studies that have drawn conclusions on the basis of such strongly biased analysis. CONTACT: cathal.seoighe@nuigalway.ie.

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Informed and Automated k-Mer Size Selection for Genome Assembly.

Publication Date: 2013 Jun 3 PMID: 23732276
Authors: Chikhi, R. - Medvedev, P.
Journal: Bioinformatics

MOTIVATION: Motivation: Genome assembly tools based on the de Bruijn graph framework rely on a parameter k, which represents a trade-off between several competing effects that are difficult to quantify. There is currently a lack of tools that would automatically estimate the best k to use and/or quickly generate histograms of k-mer abundances that would allow the user to make an informed decision. RESULTS: We develop a fast and accurate sampling method that constructs approximate abundance histograms with a several orders of magnitude performance improvement over traditional methods. We then present a fast heuristic that uses the generated abundance histograms for putative k values to estimate the best possible value of k. We test the effectiveness of our tool using diverse sequencing datasets and find that its choice of k leads to some of the best assemblies. AVAILABILITY: Our tool KmerGenie is freely available at: http://kmergenie.bx.psu.edu/ CONTACT: chikhi@psu.edu.

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Relating Genes to Function: Identifying Enriched Transcription Factors using the ENCODE ChIP-Seq Significance Tool.

Publication Date: 2013 Jun 3 PMID: 23732275
Authors: Auerbach, R. K. - Chen, B. - Butte, A. J.
Journal: Bioinformatics

MOTIVATION: Biological analysis has shifted from identifying genes to mapping these genes to biological function. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses.Implementation: The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari, and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu.

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AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification.

Publication Date: 2013 Jun 3 PMID: 23732274
Authors: Dai, L. - Tian, M. - Wu, J. - Xiao, J. - Wang, X. - Townsend, J. P. - Zhang, Z.
Journal: Bioinformatics

SUMMARY: Community curation-harnessing community intelligence in knowledge curation, bears great promise in dealing with the flood of biological knowledge. To exploit the full potential of the scientific community for knowledge curation, multiple biological wikis (bio-wikis) have been built to date. However, none of them have achieved a substantial impact on knowledge curation. One of the major limitations in bio-wikis is insufficient community participation, which is intrinsically due to lack of explicit authorship and thus no credit for community curation. To increase community curation in bio-wikis, here we develop AuthorReward, an extension to MediaWiki, to reward community-curated efforts in knowledge curation. AuthorReward quantifies researchers' contributions by properly factoring both edit quantity and quality and yields automated explicit authorship according to their quantitative contributions. AuthorReward provides bio-wikis with an authorship metric, helpful to increase community participation in bio-wikis and to achieve community curation of massive biological knowledge. AVAILABILITY: http://cbb.big.ac.cn/software CONTACT: zhangzhang@big.ac.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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SPANNER: Taxonomic assignment of sequences using pyramid matching of similarity profiles.

Publication Date: 2013 Jun 3 PMID: 23732273
Authors: Porter, M. S. - Beiko, R. G.
Journal: Bioinformatics

BACKGROUND: Homology-based taxonomic assignment is impeded by differences between the unassigned read and reference database, forcing a rank-specific classification to the closest (and possibly incorrect) reference lineage. This assignment may be correct only to a general rank (e.g., order) and incorrect below that rank (e.g., family and genus). Algorithms like LCA avoid this by varying the predicted taxonomic rank based on matches to a set of taxonomic references. LCA and related approaches can be conservative, especially if best matches are taxonomically widespread due to events such as lateral gene transfer (LGT). RESULTS: Our extension to LCA called SPANNER (Similarity Profile ANNotatER) uses the set of best homology matches (the LCA Profile) for a given sequence, and compares this profile to a set of profiles inferred from taxonomic reference organisms. SPANNER provides an assignment that is less sensitive to LGT and other confounding phenomena. In a series of trials on real and artificial datasets, SPANNER outperformed LCA-style algorithms in terms of taxonomic precision, and outperformed best BLAST at certain levels of taxonomic novelty in the dataset. We identify examples where LCA made an overly conservative prediction but SPANNER produced a more precise and correct prediction.Conclusions: By using profiles of homology matches to represent patterns of genomic similarity that arise due to vertical and lateral inheritance, SPANNER offers an effective compromise between taxonomic assignment based on best BLAST scores, and the conservative approach of LCA and similar approaches. AVAILABILITY: C++ source code and binaries are freely available at http://kiwi.cs.dal.ca/Software/SPANNER. CONTACT: beiko@cs.dal.ca.

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Drug-Target interaction prediction through Domain-Tuned Network Based Inference.

Publication Date: 2013 May 29 PMID: 23720490
Authors: Alaimo, S. - Pulvirenti, A. - Giugno, R. - Ferro, A.
Journal: Bioinformatics

MOTIVATION: The identification of Drug-Target Interaction (DTI) represents a costly and time consuming step in the drug discovery and design. Computational methods capable to predict reliable DTI play an important role in the field. Recently recommendation methods relying on Network Based Inference (NBI) have been proposed. However, such approaches implement naive topology based inference and do not take into account important features within the drug-target domain. RESULTS: In this paper we present a new Network Based Inference method, called Domain Tuned-Hybrid (DT-Hybrid), which extends a well establish recommendation technique by domain-based knowledge including drugs and targets similarity. DT-Hybrid has been extensively tested using the last version of experimentally validated drug-target interaction database obtained from DrugBank. Comparison with other recently proposed NBI methods clearly show that DT-Hybrid is capable of predicting more reliable drug-target interactions. AVAILABILITY: DT-Hybrid has been developed in R, and is available, along with all the results on the predictions, through an R package at the following url http://sites.google.com/site/ehybridalgo/ CONTACT: apulvirenti@dmi.unict.it.

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Improved Image Alignment Method in application to X-ray Images and Biological Images.

Publication Date: 2013 May 29 PMID: 23720489
Authors: Wang, C. W. - Chen, H. C.
Journal: Bioinformatics

MOTIVATION: Alignment of medical images is a vital component of a large number of applications throughout the clinical track of events; not only within clinical diagnostic settings, but prominently so in the area of planning, consummation and evaluation of surgical and radiotherapeutical procedures. However, image registration of medical images is challenging due to variations on data appearance, imaging artifacts and complex data deformation problems. Hence, the aim of this study is to develop a robust image alignment method for medical images. RESULTS: An improved image registration method is proposed, and the method is evaluated with two types of medical data, including biological microscopic tissue images and dental x-ray images, and compared with five state-of-the-art image registration techniques. The experimental results show that the presented method consistently performs well on both types of medical images, achieving 88.44% and 88.93% averaged registration accuracies for biological tissue images and x-ray images respectively and outperforms the benchmark methods. Based on the Tukey's HSD and LSD tests, the presented method performs significantly better than all existing methods (p
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COPRED: Prediction of fold, GO molecular function and functional residues at the domain level.

Publication Date: 2013 May 29 PMID: 23720488
Authors: Lopez, D. - Pazos, F.
Journal: Bioinformatics

SUMMARY: Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked.Availability and Implementation: COPRED can be freely accessed at: http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein three-dimensional structures. The web site includes a detailed help section and usage examples. CONTACT: Florencio Pazos (pazos@cnb.csic.es).

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EpiCombFlu: Exploring known influenza epitopes and their combination to design universal influenza vaccine.

Publication Date: 2013 May 28 PMID: 23716197
Authors: Jaiswal, V. - Chanumolu, S. K. - Sharma, P. - Chauhan, R. S. - Rout, C.
Journal: Bioinformatics

Motivation & RESULT: Influenza is responsible for half-million deaths annually and vaccination is the best preventive measure against this pervasive health problem. Influenza vaccines developed from surveillance data of each season are strain-specific, therefore, unable to provide protection against pandemic strains arising from antigenic shift and drift. Seasonal epidemics and occasional pandemics of influenza have created a need for universal influenza vaccine (UIV). Researchers have shown that combination of conserved epitopes has potential to be used as UIV. In the present work, available data on strains, proteins, epitopes and their associated information were used to develop a web-resource, 'EpiCombFlu' which can explore different influenza epitopes and their combinations for conservation among different strains, population coverage, and immune response for vaccine design. Forward selection algorithm was implemented in EpiCombFlu to select optimum combination of epitopes which may be expressed and evaluated as potential UIV. The web-resource is freely available at http://117.211.115.67/influenza/home.html. CONTACT: chittaranjan.rout@juit.ac.in.

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HitPick: a web server for hit identification and target prediction of chemical screenings.

Publication Date: 2013 May 28 PMID: 23716196
Authors: Liu, X. - Vogt, I. - Haque, T. - Campillos, M.
Journal: Bioinformatics

MOTIVATION: High-throughput phenotypic assays reveal information about the molecules that modulate biological processes such as a disease phenotype and a signaling pathway. In these assays, the identification of hits along with their molecular targets is critical to understand the chemical activities modulating the biological system. Here, we present HitPick, a web server for identification of hits in high-throughput chemical screenings and prediction of their molecular targets. HitPick applies the B-score method for hit identification and a newly developed approach combining 1-Nearest-Neighbour (1NN) similarity searching and Laplacian-modified naive Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed. AVAILABILITY: The server can be accessed at http://mips.helmholtz-muenchen.de/proj/hitpick CONTACT: monica.campillos@helmholtz-muenchen.de.

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A method for finding consensus breakpoints in the cancer genome from copy number data.

Publication Date: 2013 May 28 PMID: 23716195
Authors: Tolosi, L. - Theissen, J. - Halachev, K. - Hero, B. - Berthold, F. - Lengauer, T.
Journal: Bioinformatics

MOTIVATION: Recurrent DNA breakpoints in cancer genomes indicate the presence of critical functional elements for tumor development. Identifying them can help determine new therapeutic targets. High-dimensional DNA microarray experiments like arrayCGH afford the identification of DNA copy number breakpoints with high precision, offering a solid basis for computational estimation of recurrent breakpoint locations. RESULTS: We introduce a method for identification of recurrent breakpoints (consensus breakpoints) from copy number aberration datasets. The method is based on weighted kernel counting of breakpoints around genomic locations. Counts larger than expected by chance are considered significant. We show that the consensus breakpoints facilitate consensus segmentation of the samples. We apply our method to three arrayCGH datasets and show that by using consensus segmentation we achieve significant dimension reduction, which is useful for the task of prediction of tumor phenotype based on copy number data. We use our approach for classification of neuroblastoma tumors from different age groups and confirm the recent recommendation for the choice of age cutoff for differential treatment of 18 months. We also investigate the (epi)genetic properties at consensus breakpoint locations for seven datasets and show enrichment in overlap with important functional genomic regions. AVAILABILITY: Implementation in R of our approach can be found at http://www.mpi-inf.mpg.de/ approximately laura/FeatureGrouping.html. CONTACT: laura@mpi-inf.mpg.de.

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Mutascope: Sensitive Detection of Somatic Mutations from Deep Amplicon Sequencing.

Publication Date: 2013 May 27 PMID: 23712659
Authors: Yost, S. E. - Alakus, H. - Matsui, H. - Schwab, R. B. - Jepsen, K. - Frazer, K. A. - Harismendy, O.
Journal: Bioinformatics

SUMMARY: We present Mutascope, a sequencing analysis pipeline specifically developed for the identification of somatic variants present at low allelic fraction from high-throughput sequencing of amplicons from matched tumor-normal specimen. Using datasets reproducing tumor genetic heterogeneity, we demonstrate that Mutascope has a higher sensitivity and generates fewer false positive calls than tools designed for shotgun sequencing or diploid genomes. AVAILABILITY: Freely available on the web at http://sourceforge.net/projects/mutascope/ CONTACT: oharismendy@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary Information is available at Bioinformatics online.

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ChemMapper: a versatile web server for exploring pharmacology and chemical structure association based on molecular 3D similarity method.

Publication Date: 2013 May 27 PMID: 23712658
Authors: Gong, J. - Cai, C. - Liu, X. - Ku, X. - Jiang, H. - Gao, D. - Li, H.
Journal: Bioinformatics

SUMMARY: ChemMapper is an online platform to predict polypharmacology effect and mode of action for small molecules based on 3D similarity computation. ChemMapper collects over 350,000 chemical structures with bioactivities and associated target annotations (as well as over 3,000,000 non-annotated compounds for virtual screening). Taking the user-provided chemical structure as the query, the top most similar compounds in terms of 3D similarity are returned with associated pharmacology annotations. ChemMapper is designed to provide versatile services in a variety of chemogenomics, drug repurposing, polypharmacology, novel bioactive compounds identification, and scaffold hopping studies. AVAILABILITY: http://lilab.ecust.edu.cn/chemmapper/ CONTACT: xfliu@ecust.edu.cn or hlli@ecust.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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DeMix: Deconvolution for Mixed Cancer Transcriptomes Using Raw Measured Data.

Publication Date: 2013 May 27 PMID: 23712657
Authors: Ahn, J. - Yuan, Y. - Parmigiani, G. - Suraokar, M. B. - Diao, L. - Wistuba, I. I. - Wang, W.
Journal: Bioinformatics

MOTIVATION: Tissue samples of both tumor cells mixed with stromal cells cause underdetection of gene expression signatures associated with cancer prognosis or response to treatment. In silico dissection of mixed cell samples is essential for analyzing expression data generated in cancer studies. Currently, a systematic approach is lacking to address three challenges in computational deconvolution: 1) violation of linear addition of expression levels from multiple tissues when log-transformed microarray data are used; 2) estimation of both tumor proportion and tumor-specific expression, when neither is known a priori; and 3) estimation of expression profiles for individual patients. RESULTS: We have developed a statistical method for deconvolving mixed cancer transcriptomes, DeMix, which addresses the above issues in array-based expression data. We demonstrate the performance of our model in synthetic and real, publicly available, datasets. DeMix can be applied to ongoing biomarker-based clinical studies and to the vast expression datasets previously generated from mixed tumor and stromal cell samples. AVAILABILITY: All codes are written in C and integrated into an R function, which is available at http://odin.mdacc.tmc.edu/ approximately wwang7/DeMix.html. CONTACT: wwang7@mdanderson.orgSupplemental information is available online.

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viRome: an R package for the visualization and analysis of viral small RNA sequence datasets.

Publication Date: 2013 May 24 PMID: 23709497
Authors: Watson, M. - Schnettler, E. - Kohl, A.
Journal: Bioinformatics

SUMMARY: RNA interference (RNAi) is known to play an important part in defense against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools which can condense, analyse and display the resulting data. Here we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports.Availability and implementation: viRome is released under the BSD license as a package for R available for both Windows and Linux http://virome.sf.net CONTACT: mick.watson@roslin.ed.ac.uk SUPPLEMENTARY INFORMATION: Additional information and a tutorial is available on the ARK-Genomics website: http://www.ark-genomics.org/bioinformatics/virome.

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PIUS: Peptide Identification by Unbiased Search.

Publication Date: 2013 May 24 PMID: 23709496
Authors: Costa, E. - Menschaert, G. - Luyten, W. - De Grave, K. - Ramon, J.
Journal: Bioinformatics

SUMMARY: We present PIUS, a tool that identifies peptides from tandem mass spectrometry data by analyzing the six-frame translation of a complete genome. It differs from earlier studies that have performed such a genomic search in two ways: (1) it considers a larger search space; and (2) it is designed for natural peptide identification rather than proteomics. Differently from other peptidomics tools designed for genome-wide searches, PIUS does not limit the analysis to a set of sequences that match a list of de novo reconstructions. AVAILABILITY: Source code, executables, and a detailed technical report are freely available at http://dtai.cs.kuleuven.be/ml/systems/pius. CONTACT: eduardo.costa@cs.kuleuven.be.

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miRTCat: a comprehensive map of human and mouse microRNA target sites including non-canonical nucleation bulges.

Publication Date: 2013 May 24 PMID: 23709495
Authors: Kim, K. K. - Ham, J. - Wook Chi, S.
Journal: Bioinformatics

SUMMARY: MicroRNAs (miRNAs) regulate various biological functions by binding hundreds of transcripts to impart post-transcriptional repression. Recently, by applying a transcriptome-wide experimental method for identifying miRNA target sites (Ago HITS-CLIP), a novel non-canonical target site, named "nucleation bulge", was discovered as widespread, functional and evolutionally conserved. Although such non-canonical nucleation bulges have been proven to be predictive by using "pivot pairing rule" and sequence conservation, this approach has not been applied yet. To facilitate the functional studies of non-canonical miRNA targets, we implement miRTCat: a comprehensive searchable map of miRNA target sites including non-canonical nucleation bulges, not only mapped in experimentally verified miRNA-bound regions but also predicted in all 3' untranslated regions (3'UTRs) derived from human and mouse ( approximately 15.6% as expected false-positives). AVAILABILITY: http://ion.skku.edu/mirtcat CONTACT: swchi@skku.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Triplex: an R/Bioconductor package for identification and visualization of potential intramolecular triplex patterns in DNA sequences.

Publication Date: 2013 May 24 PMID: 23709494
Authors: Hon, J. - Martinek, T. - Rajdl, K. - Lexa, M.
Journal: Bioinformatics

MOTIVATION: Upgrade and integration of triplex software into the R/Bioconductor framework. RESULTS: We combined a previously published implementation of a triplex DNA search algorithm with visualization to create a versatile R/Bioconductor package "triplex". The new package provides functions that can be used to search Bioconductor genomes and other DNA sequence data for occurrence of nucleotide patterns capable of forming intramolecular triplexes (H-DNA). Functions producing 2-D and 3-D diagrams of the identified triplexes allow instant visualization of the search results. Leveraging the power of Biostrings and GRanges classes, the results get fully integrated into the existing Bioconductor framework, allowing their passage to other Genome visualization and annotation packages, such as GenomeGraphs, rtracklayer or Gviz. AVAILABILITY: R package "triplex" is available from Bioconductor (bioconductor.org). CONTACT: lexa@fi.muni.cz.

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Assembling the 20 Gb white spruce (Picea glauca) genome from whole-genome shotgun sequencing data.

Publication Date: 2013 May 22 PMID: 23698863
Authors: Birol, I. - Raymond, A. - Jackman, S. D. - Pleasance, S. - Coope, R. - Taylor, G. A. - Yuen, M. M. - Keeling, C. I. - Brand, D. - Vandervalk, B. P. - Kirk, H. - Pandoh, P. - Moore, R. A. - Zhao, Y. - Mungall, A. J. - Jaquish, B. - Yanchuk, A. - Ritland, C. - Boyle, B. - Bousquet, J. - Ritland, K. - Mackay, J. - Bohlmann, J. - Jones, S. J.
Journal: Bioinformatics

White spruce (Picea glauca) is a dominant conifer of the boreal forests of North America, and providing genomics resources for this commercially valuable tree will help improve forest management and conservation efforts. Sequencing and assembling the large and highly repetitive spruce genome though pushes the boundaries of the current technology. Here, we describe a whole-genome shotgun sequencing strategy using two Illumina sequencing platforms and an assembly approach using the ABySS software. We report a 20.8 giga base pairs draft genome in 4.9 million scaffolds, with a scaffold N50 of 20 356 bp. We demonstrate how recent improvements in the sequencing technology, especially increasing read lengths and paired end reads from longer fragments have a major impact on the assembly contiguity. We also note that scalable bioinformatics tools are instrumental in providing rapid draft assemblies. AVAILABILITY: The Picea glauca genome sequencing and assembly data are available through NCBI (Accession#: ALWZ0100000000 PID: PRJNA83435). http://www.ncbi.nlm.nih.gov/bioproject/83435. CONTACT: ibirol@bcgsc.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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ShereKhan - Calculating exchange parameters in relaxation dispersion data from CPMG experiments.

Publication Date: 2013 May 21 PMID: 23698862
Authors: Mazur, A. - Hammesfahr, B. - Griesinger, C. - Lee, D. - Kollmar, M.
Journal: Bioinformatics

SUMMARY: Dynamics governing the function of biomolecule is usually described as exchange processes and can be monitored at atomic resolution with nuclear magnetic resonance (NMR) relaxation dispersion data. Here, we present a new tool for the analysis of CPMG relaxation dispersion profiles (ShereKhan). The web-interface to ShereKhan provides a user-friendly environment for the analysis. AVAILABILITY: A stable version of ShereKhan, the web-application, and documentation are available at http://sherekhan.bionmr.org. CONTACT: dole@nmr.mpibpc.mpg.de, mako@nmr.mpibpc.mpg.de.

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MASS: meta-analysis of score statistics for sequencing studies.

Publication Date: 2013 May 21 PMID: 23698861
Authors: Tang, Z. Z. - Lin, D. Y.
Journal: Bioinformatics

SUMMARY: MASS is a command-line program to perform meta-analysis of sequencing studies by combining the score statistics from multiple studies. It implements three types of multivariate tests that encompass all commonly used association tests for rare variants. The input file can be generated from the accompanying software SCORE-Seq. This bundle of programs allows analysis of large sequencing studies in a time and memory efficient manner.Availability and implementation: MASS and SCORE-Seq, including documentations and executables, are available at http://dlin.web.unc.edu/software/. CONTACT: lin@bios.unc.edu.

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TiPs: A database of therapeutic targets in pathogens and associated tools.

Publication Date: 2013 May 21 PMID: 23698860
Authors: Lepore, R. - Tramontano, A. - Via, A.
Journal: Bioinformatics

MOTIVATION: The need for new drugs and new targets is particularly compelling in an era that is witnessing an alarming increase of drug resistance in human pathogens. The identification of new targets of known drugs is a promising approach, which has proven successful in several cases. Here, we describe a database that includes information on 5153 putative drug-target pairs for 150 human pathogens derived from available drug-target crystallographic complexes.Availability and implementation: The TiPs Database is freely available at http://biocomputing.it/tips CONTACT: anna.tramontano@uniroma1.it, allegra.via@uniroma1.it.

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NETAL: a new graph-based method for global alignment of protein-protein interaction networks.

Publication Date: 2013 May 21 PMID: 23696650
Authors: Neyshabur, B. - Khadem, A. - Hashemifar, S. - Arab, S. S.
Journal: Bioinformatics

MOTIVATION: The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together. RESULTS: We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein-protein interaction networks. AVAILABILITY: Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal. CONTACT: sh.arab@modares.ac.ir SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Specificity control for read alignments using an artificial reference genome-guided false discovery rate.

Publication Date: 2013 May 30 PMID: 23685787
Authors: Giese, S. H. - Zickmann, F. - Renard, B. Y.
Journal: Bioinformatics

MOTIVATION: Accurate estimation, comparison and evaluation of read mapping error rates is a crucial step in the processing of next-generation sequencing data, as further analysis steps and interpretation assume the correctness of the mapping results. Current approaches are either focused on sensitivity estimation and thereby disregard specificity or are based on read simulations. Although continuously improving, read simulations are still prone to introduce a bias into the mapping error quantitation and cannot capture all characteristics of an individual dataset. RESULTS: We introduce ARDEN (artificial reference driven estimation of false positives in next-generation sequencing data), a novel benchmark method that estimates error rates of read mappers based on real experimental reads, using an additionally generated artificial reference genome. It allows a dataset-specific computation of error rates and the construction of a receiver operating characteristic curve. Thereby, it can be used for optimization of parameters for read mappers, selection of read mappers for a specific problem or for filtering alignments based on quality estimation. The use of ARDEN is demonstrated in a general read mapper comparison, a parameter optimization for one read mapper and an application example in single-nucleotide polymorphism discovery with a significant reduction in the number of false positive identifications. AVAILABILITY: The ARDEN source code is freely available at http://sourceforge.net/projects/arden/. CONTACT: renardb@rki.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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MEME-LaB: motif analysis in clusters.

Publication Date: 2013 May 24 PMID: 23681125
Authors: Brown, P. - Baxter, L. - Hickman, R. - Beynon, J. - Moore, J. D. - Ott, S.
Journal: Bioinformatics

SUMMARY: Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets. AVAILABILITY: MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/. CONTACT: p.e.brown@warwick.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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ACCUSA2: multi-purpose SNV calling enhanced by probabilistic integration of quality scores.

Publication Date: 2013 Jun 7 PMID: 23681124
Authors: Piechotta, M. - Dieterich, C.
Journal: Bioinformatics

SUMMARY: Direct comparisons of assembled short-read stacks are one way to identify single-nucleotide variants. Single-nucleotide variant detection is especially challenging across samples with different read depths (e.g. RNA-Seq) and high-background levels (e.g. selection experiments). We present ACCUSA2 to identify variant positions where nucleotide frequency spectra differ between two samples. To this end, ACCUSA2 integrates quality scores for base calling and read mapping into a common framework. Our benchmarks demonstrate that ACCUSA2 is superior to a state-of-the-art SNV caller in situations of diverging read depths and reliably detects subtle differences among sample nucleotide frequency spectra. Additionally, we show that ACCUSA2 is fast and robust against base quality score deviations. AVAILABILITY: ACCUSA2 is available free of charge to academic users and may be obtained from https://bbc.mdc-berlin.de/software. CONTACT: christoph.dieterich@mdc-berlin.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

Publication Date: 2013 Jun 8 PMID: 23681123
Authors: Ollion, J. - Cochennec, J. - Loll, F. - Escude, C. - Boudier, T.
Journal: Bioinformatics

MOTIVATION: The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. RESULTS: Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. AVAILABILITY: TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. CONTACT: thomas.boudier@snv.jussieu.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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CAPITO--a web server-based analysis and plotting tool for circular dichroism data.

Publication Date: 2013 Jun 7 PMID: 23681122
Authors: Wiedemann, C. - Bellstedt, P. - Gorlach, M.
Journal: Bioinformatics

MOTIVATION: Circular dichroism (CD) spectroscopy is one of the most versatile tools to study protein folding and to validate the proper fold of purified proteins. Here, we aim to provide a readily accessible, user-friendly and platform-independent tool capable of analysing multiple CD datasets of virtually any format and returning results as high-quality graphical output to the user. RESULTS: CAPITO (CD Anaylsis and Plotting Tool) is a novel web server-based tool for analysing and plotting CD data. It allows reliable estimation of secondary structure content utilizing different approaches. CAPITO accepts multiple CD datasets and, hence, is well suited for a wide application range such as the analysis of temperature or pH-dependent (un)folding and the comparison of mutants. AVAILABILITY: http://capito.nmr.fli-leibniz.de. CONTACT: cwiede@fli-leibniz.de or mago@fli-leibniz.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies.

Publication Date: 2013 Jun 8 PMID: 23681121
Authors: Fu, C. - Jin, G. - Gao, J. - Zhu, R. - Ballesteros-Villagrana, E. - Wong, S. T.
Journal: Bioinformatics

SUMMARY: Systematic studies of drug repositioning require the integration of multi-level drug data, including basic chemical information (such as SMILES), drug targets, target-related signaling pathways, clinical trial information and Food and Drug Administration (FDA)-approval information, to predict new potential indications of existing drugs. Currently available databases, however, lack query support for multi-level drug information and thus are not designed to support drug repositioning studies. DrugMap Central (DMC), an online tool, is developed to help fill the gap. DMC enables the users to integrate, query, visualize, interrogate, and download multi-level data of known drugs or compounds quickly for drug repositioning studies all within one system.Availability: DMC is accessible at http://r2d2drug.org/DMC.aspx.Contact: STWong@tmhs.org.

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ReviSTER: an automated pipeline to revise misaligned reads to simple tandem repeats.

Publication Date: 2013 Jun 7 PMID: 23677944
Authors: Tae, H. - McMahon, K. W. - Settlage, R. E. - Bavarva, J. H. - Garner, H. R.
Journal: Bioinformatics

MOTIVATION: Simple tandem repeats are highly variable genetic elements and widespread in genomes of many organisms. Next-generation sequencing technologies have enabled a robust comparison of large numbers of simple tandem repeat loci; however, analysis of their variation using traditional sequence analysis approaches still remains limiting and problematic due to variants occurring in repeat sequences confusing alignment programs into mapping sequence reads to incorrect loci when the sequence reads are significantly different from the reference sequence. RESULTS: We have developed a program, ReviSTER, which is an automated pipeline using a 'local mapping reference reconstruction method' to revise mismapped or partially misaligned reads at simple tandem repeat loci. RevisSTER estimates alleles of repeat loci using a local alignment method and creates temporary local mapping reference sequences, and finally remaps reads to the local mapping references. Using this approach, ReviSTER was able to successfully revise reads misaligned to repeat loci from both simulated data and real data. AVAILABILITY: ReviSTER is open-source software available at http://revister.sourceforge.net. CONTACT: garner@vbi.vt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Updating RNA-Seq analyses after re-annotation.

Publication Date: 2013 May 21 PMID: 23677943
Authors: Roberts, A. - Schaeffer, L. - Pachter, L.
Journal: Bioinformatics

The estimation of isoform abundances from RNA-Seq data requires a time-intensive step of mapping reads to either an assembled or previously annotated transcriptome, followed by an optimization procedure for deconvolution of multi-mapping reads. These procedures are essential for downstream analysis such as differential expression. In cases where it is desirable to adjust the underlying annotation, for example, on the discovery of novel isoforms or errors in existing annotations, current pipelines must be rerun from scratch. This makes it difficult to update abundance estimates after re-annotation, or to explore the effect of changes in the transcriptome on analyses. We present a novel efficient algorithm for updating abundance estimates from RNA-Seq experiments on re-annotation that does not require re-analysis of the entire dataset. Our approach is based on a fast partitioning algorithm for identifying transcripts whose abundances may depend on the added or deleted isoforms, and on a fast follow-up approach to re-estimating abundances for all transcripts. We demonstrate the effectiveness of our methods by showing how to synchronize RNA-Seq abundance estimates with the daily RefSeq incremental updates. Thus, we provide a practical approach to maintaining relevant databases of RNA-Seq derived abundance estimates even as annotations are being constantly revised.Availability and implementation: Our methods are implemented in software called ReXpress and are freely available, together with source code, at http://bio.math.berkeley.edu/ReXpress/. CONTACT: lpachter@math.berkeley.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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PconsD: ultra rapid, accurate model quality assessment for protein structure prediction.

Publication Date: 2013 Jun 12 PMID: 23677942
Authors: Skwark, M. J. - Elofsson, A.
Journal: Bioinformatics

SUMMARY: Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy. AVAILABILITY: The source code for PconsD is freely available at http://d.pcons.net/. Supplementary benchmarking data are also available there. CONTACT: arne@bioinfo.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Relation between sequence and structure in membrane proteins.

Publication Date: 2013 May 30 PMID: 23677941
Authors: Olivella, M. - Gonzalez, A. - Pardo, L. - Deupi, X.
Journal: Bioinformatics

MOTIVATION: Integral polytopic membrane proteins contain only two types of folds in their transmembrane domains: alpha-helix bundles and beta-barrels. The increasing number of available crystal structures of these proteins permits an initial estimation of how sequence variability affects the structure conservation in their transmembrane domains. We, thus, aim to determine the pairwise sequence identity necessary to maintain the transmembrane molecular architectures compatible with the hydrophobic nature of the lipid bilayer. RESULTS: Root-mean-square deviation (rmsd) and sequence identity were calculated from the structural alignments of pairs of homologous polytopic membrane proteins sharing the same fold. Analysis of these data reveals that transmembrane segment pairs with sequence identity in the so-called 'twilight zone' (20-35%) display high-structural similarity (rmsd < 1.5 A). Moreover, a large group of beta-barrel pairs with low-sequence identity (<20%) still maintain a close structural similarity (rmsd < 2.5 A). Thus, we conclude that fold preservation in transmembrane regions requires less sequence conservation than for globular proteins. These findings have direct implications in homology modeling of evolutionary-related membrane proteins. CONTACT: Mireia.Olivella@uvic.cat or Xavier.Deupi@psi.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Identification of hidden relationships from the coupling of Hydrophobic Cluster Analysis and Domain Architecture information.

Publication Date: 2013 Jun 8 PMID: 23677940
Authors: Faure, G. - Callebaut, I.
Journal: Bioinformatics

MOTIVATION: Describing domain architecture is a critical step in the functional characterization of proteins. However, some orphan domains do not match any profile stored in dedicated domain databases and are thereby difficult to analyze. RESULTS: We present here an original novel approach, called TREMOLO-HCA, for the analysis of orphan domain sequences and inspired from our experience in the use of Hydrophobic Cluster Analysis (HCA). Hidden relationships between protein sequences can be more easily identified from the PSI-BLAST results, using information on domain architecture, HCA plots and the conservation degree of amino acids that may participate in the protein core. This can lead to reveal remote relationships with known families of domains, as illustrated here with the identification of a hidden Tudor tandem in the human BAHCC1 protein and a hidden ET domain in the Saccharomyces cerevisiae Taf14p and human AF9 proteins. The results obtained in such a way are consistent with those provided by HHPRED, based on pairwise comparisons of HHMs. Our approach can, however, be applied even in absence of domain profiles or known 3D structures for the identification of novel families of domains. It can also be used in a reverse way for refining domain profiles, by starting from known protein domain families and identifying highly divergent members, hitherto considered as orphan. AVAILABILITY: We provide a possible integration of this approach in an open TREMOLO-HCA package, which is fully implemented in python v2.7 and is available on request. Instructions are available at http://www.impmc.upmc.fr/ approximately callebau/tremolohca.html. CONTACT: isabelle.callebaut@impmc.upmc.fr SUPPLEMENTARY INFORMATION: Supplementary Data are available at Bioinformatics online.

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A hierarchical model of transcriptional dynamics allows robust estimation of transcription rates in populations of single cells with variable gene copy number.

Publication Date: 2013 Jun 15 PMID: 23677939
Authors: Woodcock, D. J. - Vance, K. W. - Komorowski, M. - Koentges, G. - Finkenstadt, B. - Rand, D. A.
Journal: Bioinformatics

MOTIVATION: cis-regulatory DNA sequence elements, such as enhancers and silencers, function to control the spatial and temporal expression of their target genes. Although the overall levels of gene expression in large cell populations seem to be precisely controlled, transcription of individual genes in single cells is extremely variable in real time. It is, therefore, important to understand how these cis-regulatory elements function to dynamically control transcription at single-cell resolution. Recently, statistical methods have been proposed to back calculate the rates involved in mRNA transcription using parameter estimation of a mathematical model of transcription and translation. However, a major complication in these approaches is that some of the parameters, particularly those corresponding to the gene copy number and transcription rate, cannot be distinguished; therefore, these methods cannot be used when the copy number is unknown. RESULTS: Here, we develop a hierarchical Bayesian model to estimate biokinetic parameters from live cell enhancer-promoter reporter measurements performed on a population of single cells. This allows us to investigate transcriptional dynamics when the copy number is variable across the population. We validate our method using synthetic data and then apply it to quantify the function of two known developmental enhancers in real time and in single cells. AVAILABILITY: Supporting information is submitted with the article. CONTACT: d.j.woodcock@warwick.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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MetPP: a computational platform for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

Publication Date: 2013 Jun 5 PMID: 23665844
Authors: Wei, X. - Shi, X. - Koo, I. - Kim, S. - Schmidt, R. H. - Arteel, G. E. - Watson, W. H. - McClain, C. - Zhang, X.
Journal: Bioinformatics

MOTIVATION: Due to the high complexity of metabolome, the comprehensive 2D gas chromatography time-of-flight mass spectrometry (GCxGC-TOF MS) is considered as a powerful analytical platform for metabolomics study. However, the applications of GCxGC-TOF MS in metabolomics are not popular owing to the lack of bioinformatics system for data analysis. RESULTS: We developed a computational platform entitled metabolomics profiling pipeline (MetPP) for analysis of metabolomics data acquired on a GCxGC-TOF MS system. MetPP can process peak filtering and merging, retention index matching, peak list alignment, normalization, statistical significance tests and pattern recognition, using the peak lists deconvoluted from the instrument data as its input. The performance of MetPP software was tested with two sets of experimental data acquired in a spike-in experiment and a biomarker discovery experiment, respectively. MetPP not only correctly aligned the spiked-in metabolite standards from the experimental data, but also correctly recognized their concentration difference between sample groups. For analysis of the biomarker discovery data, 15 metabolites were recognized with significant concentration difference between the sample groups and these results agree with the literature results of histological analysis, demonstrating the effectiveness of applying MetPP software for disease biomarker discovery. AVAILABILITY: The source code of MetPP is available at http://metaopen.sourceforge.net CONTACT: xiang.zhang@louisville.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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A combinatorial approach to the peptide feature matching problem for label-free quantification.

Publication Date: 2013 Jun 5 PMID: 23665772
Authors: Lin, H. - He, L. - Ma, B.
Journal: Bioinformatics

MOTIVATION: Label-free quantification is an important approach to identify biomarkers, as it measures the quantity change of peptides across different biological samples. One of the fundamental steps for label-free quantification is to match the peptide features that are detected in two datasets to each other. Although ad hoc software tools exist for the feature matching, the definition of a combinatorial model for this problem is still not available. RESULTS: A combinatorial model is proposed in this article. Each peptide feature contains a mass value and a retention time value, which are used to calculate a matching weight between a pair of features. The feature matching is to find the maximum-weighted matching between the two sets of features, after applying a to-be-computed time alignment function to all the retention time values of one set of the features. This is similar to the maximum matching problem in a bipartite graph. But we show that the requirement of time alignment makes the problem NP-hard. Practical algorithms are also provided. Experiments on real data show that the algorithm compares favorably with other existing methods. CONTACT: binma@uwaterloo.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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GAGE-B: an evaluation of genome assemblers for bacterial organisms.

Publication Date: 2013 Jun 5 PMID: 23665771
Authors: Magoc, T. - Pabinger, S. - Canzar, S. - Liu, X. - Su, Q. - Puiu, D. - Tallon, L. J. - Salzberg, S. L.
Journal: Bioinformatics

MOTIVATION: A large and rapidly growing number of bacterial organisms have been sequenced by the newest sequencing technologies. Cheaper and faster sequencing technologies make it easy to generate very high coverage of bacterial genomes, but these advances mean that DNA preparation costs can exceed the cost of sequencing for small genomes. The need to contain costs often results in the creation of only a single sequencing library, which in turn introduces new challenges for genome assembly methods. RESULTS: We evaluated the ability of multiple genome assembly programs to assemble bacterial genomes from a single, deep-coverage library. For our comparison, we chose bacterial species spanning a wide range of GC content and measured the contiguity and accuracy of the resulting assemblies. We compared the assemblies produced by this very high-coverage, one-library strategy to the best assemblies created by two-library sequencing, and we found that remarkably good bacterial assemblies are possible with just one library. We also measured the effect of read length and depth of coverage on assembly quality and determined the values that provide the best results with current algorithms. CONTACT: salzberg@jhu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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International society for computational biology honors goncalo abecasis with top bioinformatics/computational biology award for 2013.

Publication Date: 2013 Jun 15 PMID: 23661697
Authors: Fogg, C. N. - Kovats, D. E.
Journal: Bioinformatics

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pyDockWEB: a web server for rigid-body protein-protein docking using electrostatics and desolvation scoring.

Publication Date: 2013 Jun 3 PMID: 23661696
Authors: Jimenez-Garcia, B. - Pons, C. - Fernandez-Recio, J.
Journal: Bioinformatics

SUMMARY: pyDockWEB is a web server for the rigid-body docking prediction of protein-protein complex structures using a new version of the pyDock scoring algorithm. We use here a new custom parallel FTDock implementation, with adjusted grid size for optimal FFT calculations, and a new version of pyDock, which dramatically speeds up calculations while keeping the same predictive accuracy. Given the 3D coordinates of two interacting proteins, pyDockWEB returns the best docking orientations as scored mainly by electrostatics and desolvation energy.Availability and implementation: The server does not require registration by the user and is freely accessible for academics at http://life.bsc.es/servlet/pydock CONTACT: juanf@bsc.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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iFUSE: integrated fusion gene explorer.

Publication Date: 2013 Jun 7 PMID: 23661695
Authors: Hiltemann, S. - McClellan, E. A. - van Nijnatten, J. - Horsman, S. - Palli, I. - Teles Alves, I. - Hartjes, T. - Trapman, J. - van der Spek, P. - Jenster, G. - Stubbs, A.
Journal: Bioinformatics

SUMMARY: We present iFUSE (integrated fusion gene explorer), an online visualization tool that provides a fast and informative view of structural variation data and prioritizes those breaks likely representing fusion genes. This application uses calculated break points to determine fusion genes based on the latest annotation for genomic sequence information, and where relevant the structural variation (SV) events are annotated with predicted RNA and protein sequences. iFUSE takes as input a Complete Genomics (CG) junction file, a FusionMap fusion detection report file or a file already analysed and annotated by the iFUSE application on a previous occasion. RESULTS: We demonstrate the use of iFUSE with case studies from tumour-normal SV detection derived from Complete Genomics whole-genome sequencing results. AVAILABILITY: iFUSE is available as a web service at http://ifuse.erasmusmc.nl. CONTACT: s.hiltemann@erasmusmc.nl or a.stubbs@erasmusmc.nl.

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Adaptive reference-free compression of sequence quality scores.

Publication Date: 2013 Jun 4 PMID: 23661694
Authors: Janin, L. - Rosone, G. - Cox, A. J.
Journal: Bioinformatics

MOTIVATION: Rapid technological progress in DNA sequencing has stimulated interest in compressing the vast datasets that are now routinely produced. Relatively little attention has been paid to compressing the quality scores that are assigned to each sequence, even though these scores may be harder to compress than the sequences themselves. By aggregating a set of reads into a compressed index, we find that the majority of bases can be predicted from the sequence of bases that are adjacent to them and, hence, are likely to be less informative for variant calling or other applications. The quality scores for such bases are aggressively compressed, leaving a relatively small number at full resolution. As our approach relies directly on redundancy present in the reads, it does not need a reference sequence and is, therefore, applicable to data from metagenomics and de novo experiments as well as to re-sequencing data. RESULTS: We show that a conservative smoothing strategy affecting 75% of the quality scores above Q2 leads to an overall quality score compression of 1 bit per value with a negligible effect on variant calling. A compression of 0.68 bit per quality value is achieved using a more aggressive smoothing strategy, again with a very small effect on variant calling. AVAILABILITY: Code to construct the BWT and LCP-array on large genomic data sets is part of the BEETL library, available as a github repository at git@github.com:BEETL/BEETL.git. CONTACT: acox@illumina.com.

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CMAP: Complement Map Database.

Publication Date: 2013 Jun 4 PMID: 23661693
Authors: Yang, K. - Dinasarapu, A. R. - Reis, E. S. - Deangelis, R. A. - Ricklin, D. - Subramaniam, S. - Lambris, J. D.
Journal: Bioinformatics

SUMMARY: The human complement system is increasingly perceived as an intricate protein network of effectors, inhibitors and regulators that drives critical processes in health and disease and extensively communicates with associated physiological pathways ranging from immunity and inflammation to homeostasis and development. A steady stream of experimental data reveals new fascinating connections at a rapid pace; although opening unique opportunities for research discoveries, the comprehensiveness and large diversity of experimental methods, nomenclatures and publication sources renders it highly challenging to keep up with the essential findings. With the Complement Map Database (CMAP), we have created a novel and easily accessible research tool to assist the complement community and scientists from related disciplines in exploring the complement network and discovering new connections. AVAILABILITY: http://www.complement.us/cmap. CONTACT: lambris@upenn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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FYPO: the fission yeast phenotype ontology.

Publication Date: 2013 Jun 3 PMID: 23658422
Authors: Harris, M. A. - Lock, A. - Bahler, J. - Oliver, S. G. - Wood, V.
Journal: Bioinformatics

MOTIVATION: To provide consistent computable descriptions of phenotype data, PomBase is developing a formal ontology of phenotypes observed in fission yeast. RESULTS: The fission yeast phenotype ontology (FYPO) is a modular ontology that uses several existing ontologies from the open biological and biomedical ontologies (OBO) collection as building blocks, including the phenotypic quality ontology PATO, the Gene Ontology and Chemical Entities of Biological Interest. Modular ontology development facilitates partially automated effective organization of detailed phenotype descriptions with complex relationships to each other and to underlying biological phenomena. As a result, FYPO supports sophisticated querying, computational analysis and comparison between different experiments and even between species. AVAILABILITY: FYPO releases are available from the Subversion repository at the PomBase SourceForge project page (https://sourceforge.net/p/pombase/code/HEAD/tree/phenotype_ontology/). The current version of FYPO is also available on the OBO Foundry Web site (http://obofoundry.org/). CONTACT: mah79@cam.ac.uk or vw253@cam.ac.uk.

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Detection of significantly differentially methylated regions in targeted bisulfite sequencing data.

Publication Date: 2013 Jun 4 PMID: 23658421
Authors: Hebestreit, K. - Dugas, M. - Klein, H. U.
Journal: Bioinformatics

MOTIVATION: Bisulfite sequencing is currently the gold standard to obtain genome-wide DNA methylation profiles in eukaryotes. In contrast to the rapid development of appropriate pre-processing and alignment software, methods for analyzing the resulting methylation profiles are relatively limited so far. For instance, an appropriate pipeline to detect DNA methylation differences between cancer and control samples is still required. RESULTS: We propose an algorithm that detects significantly differentially methylated regions in data obtained by targeted bisulfite sequencing approaches, such as reduced representation bisulfite sequencing. In a first step, this approach tests all target regions for methylation differences by taking spatial dependence into account. A false discovery rate procedure controls the expected proportion of incorrectly rejected regions. In a second step, the significant target regions are trimmed to the actually differentially methylated regions. This hierarchical procedure detects differentially methylated regions with increased power compared with existing methods. AVAILABILITY: R/Bioconductor package BiSeq. CONTACT: katja.hebestreit@uni-muenster.de SUPPLEMENTARY INFORMATION: Supplementary Data are available at Bioinformatics online.

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Twine: display and analysis of cis-regulatory modules.

Publication Date: 2013 May 29 PMID: 23658420
Authors: Pearson, J. C. - Crews, S. T.
Journal: Bioinformatics

SUMMARY: Many algorithms analyze enhancers for overrepresentation of known and novel motifs, with the goal of identifying binding sites for direct regulators of gene expression. Twine is a Java GUI with multiple graphical representations ('Views') of enhancer alignments that displays motifs, as IUPAC consensus sequences or position frequency matrices, in the context of phylogenetic conservation to facilitate cis-regulatory element discovery. Thresholds of phylogenetic conservation and motif stringency can be altered dynamically to facilitate detailed analysis of enhancer architecture. Views can be exported to vector graphics programs to generate high-quality figures for publication. Twine can be extended via Java plugins to manipulate alignments and analyze sequences. AVAILABILITY: Twine is freely available as a compiled Java .jar package or Java source code at http://labs.bio.unc.edu/crews/twine/. CONTACT: steve_crews@unc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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DAPPLE: a pipeline for the homology-based prediction of phosphorylation sites.

Publication Date: 2013 May 31 PMID: 23658419
Authors: Trost, B. - Arsenault, R. - Griebel, P. - Napper, S. - Kusalik, A.
Journal: Bioinformatics

SUMMARY: While many experimentally characterized phosphorylation sites exist for certain organisms, such as human, rat and mouse, few sites are known for other organisms, hampering related research efforts. We have developed a software pipeline called DAPPLE that automates the process of using known phosphorylation sites from other organisms to identify putative sites in an organism of interest. AVAILABILITY: DAPPLE is available as a web server at http://saphire.usask.ca. CONTACT: brett.trost@usask.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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PconsC: combination of direct information methods and alignments improves contact prediction.

Publication Date: 2013 Jun 6 PMID: 23658418
Authors: Skwark, M. J. - Abdel-Rehim, A. - Elofsson, A.
Journal: Bioinformatics

SUMMARY: Recently, several new contact prediction methods have been published. They use (i) large sets of multiple aligned sequences and (ii) assume that correlations between columns in these alignments can be the results of indirect interaction. These methods are clearly superior to earlier methods when it comes to predicting contacts in proteins. Here, we demonstrate that combining predictions from two prediction methods, PSICOV and plmDCA, and two alignment methods, HHblits and jackhmmer at four different e-value cut-offs, provides a relative improvement of 20% in comparison with the best single method, exceeding 70% correct predictions for one contact prediction per residue. AVAILABILITY: The source code for PconsC along with supplementary data is freely available at http://c.pcons.net/ CONTACT: arne@bioinfo.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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TrioVis: a visualization approach for filtering genomic variants of parent-child trios.

Publication Date: 2013 Jun 3 PMID: 23658417
Authors: Sakai, R. - Sifrim, A. - Vande Moere, A. - Aerts, J.
Journal: Bioinformatics

SUMMARY: TrioVis is a visual analytics tool developed for filtering on coverage and variant frequency for genomic variants from exome sequencing of parent-child trios. In TrioVis, the variant data are organized by grouping each variant based on the laws of Mendelian inheritance. Taking three Variant Call Format files as input, TrioVis allows the user to test different coverage thresholds (i.e. different levels of stringency), to find the optimal threshold values tailored to their hypotheses and to gain insights into the global effects of filtering through interaction. AVAILABILITY: Executables, source code and sample data are available at https://bitbucket.org/biovizleuven/triovis. Screencast is available at http://vimeo.com/user6757771/triovis. CONTACT: ryo.sakai@esat.kuleuven.be.

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A poor man's BLASTX--high-throughput metagenomic protein database search using PAUDA.

Publication Date: 2013 Jun 5 PMID: 23658416
Authors: Huson, D. H. - Xie, C.
Journal: Bioinformatics

SUMMARY: In the context of metagenomics, we introduce a new approach to protein database search called PAUDA, which runs approximately 10 000 times faster than BLASTX, while achieving about one-third of the assignment rate of reads to KEGG orthology groups, and producing gene and taxon abundance profiles that are highly correlated to those obtained with BLASTX. PAUDA requires <80 CPU hours to analyze a dataset of 246 million Illumina DNA reads from permafrost soil for which a previous BLASTX analysis (on a subset of 176 million reads) reportedly required 800 000 CPU hours, leading to the same clustering of samples by functional profiles. AVAILABILITY: PAUDA is freely available from: http://ab.inf.uni-tuebingen.de/software/pauda. Also supplementary method details are available from this website. CONTACT: daniel.huson@uni-tuebingen.de or xiechao@bic.nus.edu.sg.

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Evidence for the dissemination of cryptic non-coding RNAs transcribed from intronic and intergenic segments by retroposition.

Publication Date: 2013 May 29 PMID: 23652427
Authors: Hahn, Y.
Journal: Bioinformatics

MOTIVATION: Insertion of DNA segments is one mechanism by which genomes evolve. The bulk of genomic segments are now known to be transcribed into long and short non-coding RNAs (ncRNAs), promoter-associated transcripts and enhancer-templated transcripts. These various cryptic ncRNAs are thought to be dispersed in the human and other genomes by retroposition. RESULTS: In this study, I report clear evidence for dissemination of cryptic ncRNAs transcribed from intronic and intergenic segments by retroposition. I used highly stringent conditions to find recently retroposed ncRNAs that had a poly(A) tract and were flanked by target site duplication. I identified 73 instances of retroposition in the human, mouse, and rat genomes (12, 36 and 25 instances, respectively). The inserted segments, in some cases, served as a novel exon or promoter for the associated gene, resulting in novel transcript variants. Some disseminated sequences showed sequence conservation across animals, implying a possible regulatory role. My results indicate that retroposition is one of the mechanisms for dispersion of ncRNAs. I propose that these newly inserted segments may play a role in genome evolution by potentially functioning as novel exons, promoters or enhancers. CONTACT: yoonsoo.hahn@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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InterEvScore: a novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution.

Publication Date: 2013 Jun 7 PMID: 23652426
Authors: Andreani, J. - Faure, G. - Guerois, R.
Journal: Bioinformatics

MOTIVATION: Structural prediction of protein interactions currently remains a challenging but fundamental goal. In particular, progress in scoring functions is critical for the efficient discrimination of near-native interfaces among large sets of decoys. Many functions have been developed using knowledge-based potentials, but few make use of multi-body interactions or evolutionary information, although multi-residue interactions are crucial for protein-protein binding and protein interfaces undergo significant selection pressure to maintain their interactions. RESULTS: This article presents InterEvScore, a novel scoring function using a coarse-grained statistical potential including two- and three-body interactions, which provides each residue with the opportunity to contribute in its most favorable local structural environment. Combination of this potential with evolutionary information considerably improves scoring results on the 54 test cases from the widely used protein docking benchmark for which evolutionary information can be collected. We analyze how our way to include evolutionary information gradually increases the discriminative power of InterEvScore. Comparison with several previously published scoring functions (ZDOCK, ZRANK and SPIDER) shows the significant progress brought by InterEvScore. AVAILABILITY: http://biodev.cea.fr/interevol/interevscore CONTACT: guerois@cea.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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pyGenClean: efficient tool for genetic data clean up before association testing.

Publication Date: 2013 May 30 PMID: 23652425
Authors: Lemieux Perreault, L. P. - Provost, S. - Legault, M. A. - Barhdadi, A. - Dube, M. P.
Journal: Bioinformatics

SUMMARY: Genetic association studies making use of high-throughput genotyping arrays need to process large amounts of data in the order of millions of markers per experiment. The first step of any analysis with genotyping arrays is typically the conduct of a thorough data clean up and quality control to remove poor quality genotypes and generate metrics to inform and select individuals for downstream statistical analysis. We have developed pyGenClean, a bioinformatics tool to facilitate and standardize the genetic data clean up pipeline with genotyping array data. In conjunction with a source batch-queuing system, the tool minimizes data manipulation errors, accelerates the completion of the data clean up process and provides informative plots and metrics to guide decision making for statistical analysis.Availability and implementation: pyGenClean is an open source Python 2.7 software and is freely available, along with documentation and examples, from http://www.statgen.org. CONTACT: louis-philippe.lemieux.perreault@umontreal.ca or marie-pierre.dube@statgen.org.

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A universal open-source Electronic Laboratory Notebook.

Publication Date: 2013 Jun 5 PMID: 23645817
Authors: Voegele, C. - Bouchereau, B. - Robinot, N. - McKay, J. - Damiecki, P. - Alteyrac, L.
Journal: Bioinformatics

MOTIVATION: Laboratory notebooks remain crucial to the activities of research communities. With the increase in generation of electronic data within both wet and dry analytical laboratories and new technologies providing more efficient means of communication, Electronic Laboratory Notebooks (ELN) offer equivalent record keeping to paper-based laboratory notebooks (PLN). They additionally allow more efficient mechanisms for data sharing and retrieval, which explains the growing number of commercial ELNs available varying in size and scope but all are increasingly accepted and used by the scientific community. The International Agency for Research on Cancer (IARC) having already an LIMS and a Biobank Management System for respectively laboratory workflows and sample management, we have developed a free multidisciplinary ELN specifically dedicated to work notes that will be flexible enough to accommodate different types of data.Availability and implementation: Information for installation of our freeware ELN with source codes customizations are detailed in supplementary data. CONTACT: voegele@iarc.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Further Steps in TANGO: improved taxonomic assignment in metagenomics.

Publication Date: 2013 May 29 PMID: 23645816
Authors: Alonso-Alemany, D. - Barre, A. - Beretta, S. - Bonizzoni, P. - Nikolski, M. - Valiente, G.
Journal: Bioinformatics

MOTIVATION: TANGO is one of the most accurate tools for the taxonomic assignment of sequence reads. However, because of the differences in the taxonomy structures, performing a taxonomic assignment on different reference taxonomies will produce divergent results. RESULTS: We have improved the TANGO pipeline to be able to perform the taxonomic assignment of a metagenomic sample using alternative reference taxonomies, coming from different sources. We highlight the novel pre-processing step, necessary to accomplish this task, and describe the improvements in the assignment process. We present the new TANGO pipeline in details, and, finally, we show its performance on four real metagenomic datasets and also on synthetic datasets. AVAILABILITY: The new version of TANGO, including implementation improvements and novel developments to perform the assignment on different reference taxonomies, is freely available at http://sourceforge.net/projects/taxoassignment/. CONTACT: valiente@lsi.upc.edu.

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RegaDB: community-driven data management and analysis for infectious diseases.

Publication Date: 2013 Jun 1 PMID: 23645815
Authors: Libin, P. - Beheydt, G. - Deforche, K. - Imbrechts, S. - Ferreira, F. - Van Laethem, K. - Theys, K. - Carvalho, A. P. - Cavaco-Silva, J. - Lapadula, G. - Torti, C. - Assel, M. - Wesner, S. - Snoeck, J. - Ruelle, J. - De Bel, A. - Lacor, P. - De Munter, P. - Van Wijngaerden, E. - Zazzi, M. - Kaiser, R. - Ayouba, A. - Peeters, M. - de Oliveira, T. - Alcantara, L. C. - Grossman, Z. - Sloot, P. - Otelea, D. - Paraschiv, S. - Boucher, C. - Camacho, R. J. - Vandamme, A. M.
Journal: Bioinformatics

SUMMARY: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface. Availability and implementation: Source code, binaries and documentation are available on http://rega.kuleuven.be/cev/regadb. RegaDB is written in the Java programming language, using a web-service-oriented architecture. CONTACT: pieter.libin@rega.kuleuven.be.

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Self-interaction of transmembrane helices representing pre-clusters from the human single-span membrane proteins.

Publication Date: 2013 May 30 PMID: 23640719
Authors: Kirrbach, J. - Krugliak, M. - Ried, C. L. - Pagel, P. - Arkin, I. T. - Langosch, D.
Journal: Bioinformatics

MOTIVATION: Most integral membrane proteins form dimeric or oligomeric complexes. Oligomerization is frequently supported by the non-covalent interaction of transmembrane helices. It is currently not clear how many high-affinity transmembrane domains (TMD) exist in a proteome and how specific their interactions are with respect to preferred contacting faces and their underlying residue motifs. RESULTS: We first identify a threshold of 55% sequence similarity, which demarcates the border between meaningful alignments of TMDs and chance alignments. Clustering the human single-span membrane proteome using this threshold groups approximately 40% of the TMDs. The homotypic interaction of the TMDs representing the 33 largest clusters was systematically investigated under standardized conditions. The results reveal a broad distribution of relative affinities. High relative affinity frequently coincides with (i) the existence of a preferred helix-helix interface and (ii) sequence specificity as indicated by reduced affinity after mutating conserved residues. CONTACT: langosch@tum.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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miMsg: a target enrichment algorithm for predicted miR-mRNA interactions based on relative ranking of matched expression data.

Publication Date: 2013 May 31 PMID: 23640718
Authors: Rijlaarsdam, M. A. - Rijlaarsdam, D. J. - Gillis, A. J. - Dorssers, L. C. - Looijenga, L. H.
Journal: Bioinformatics

MOTIVATION: Algorithms predicting microRNA (miR)-mRNA interactions generate high numbers of possible interactions, many of which might be non-existent or irrelevant in a certain biological context. It is desirable to develop a transparent, user-friendly, unbiased tool to enrich miR-mRNA predictions. RESULTS: The miMsg algorithm uses matched miR/mRNA expression data to enrich miR-mRNA predictions. It grades interactions by the number, magnitude and significance of misplacements in the combined ranking profiles of miR/mRNA expression assessed over multiple biological samples. miMsg requires minimal user input and makes no statistical assumptions. It identified 921 out of 56 262 interactions as top scoring and significant in an actual germ cell cancer dataset. Twenty-eight miR-mRNA pairs were deemed of highest interest based on ranking by miMsg and supported by current knowledge about validated interactions and biological function. To conclude, miMsg is an effective algorithm to reduce a high number of predicted interactions to a small set of high confidence interactions for further study.Availability and Implementation: Matlab source code and datasets available at www.martinrijlaarsdam.nl/mimsg CONTACT: l.looijenga@erasmusmc.nl (homepage) SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Intervention in gene regulatory networks with maximal phenotype alteration.

Publication Date: 2013 May 30 PMID: 23630177
Authors: Yousefi, M. R. - Dougherty, E. R.
Journal: Bioinformatics

MOTIVATION: A basic issue for translational genomics is to model gene interaction via gene regulatory networks (GRNs) and thereby provide an informatics environment to study the effects of intervention (say, via drugs) and to derive effective intervention strategies. Taking the view that the phenotype is characterized by the long-run behavior (steady-state distribution) of the network, we desire interventions to optimally move the probability mass from undesirable to desirable states Heretofore, two external control approaches have been taken to shift the steady-state mass of a GRN: (i) use a user-defined cost function for which desirable shift of the steady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm. Neither approach provides an optimal control policy relative to long-run behavior. RESULTS: We use a linear programming approach to optimally shift the steady-state mass from undesirable to desirable states, i.e. optimization is directly based on the amount of shift and therefore must outperform previously proposed methods. Moreover, the same basic linear programming structure is used for both unconstrained and constrained optimization, where in the latter case, constraints on the optimization limit the amount of mass that may be shifted to 'ambiguous' states, these being states that are not directly undesirable relative to the pathology of interest but which bear some perceived risk. We apply the method to probabilistic Boolean networks, but the theory applies to any Markovian GRN. AVAILABILITY: Supplementary materials, including the simulation results, MATLAB source code and description of suboptimal methods are available at http://gsp.tamu.edu/Publications/supplementary/yousefi13b. CONTACT: edward@ece.tamu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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BioBlend: automating pipeline analyses within Galaxy and CloudMan.

Publication Date: 2013 Jun 7 PMID: 23630176
Authors: Sloggett, C. - Goonasekera, N. - Afgan, E.
Journal: Bioinformatics

SUMMARY: We present BioBlend, a unified API in a high-level language (python) that wraps the functionality of Galaxy and CloudMan APIs. BioBlend makes it easy for bioinformaticians to automate end-to-end large data analysis, from scratch, in a way that is highly accessible to collaborators, by allowing them to both provide the required infrastructure and automate complex analyses over large datasets within the familiar Galaxy environment.Availability and implementation: http://bioblend.readthedocs.org/. Automated installation of BioBlend is available via PyPI (e.g. pip install bioblend). Alternatively, the source code is available from the GitHub repository (https://github.com/afgane/bioblend) under the MIT open source license. The library has been tested and is working on Linux, Macintosh and Windows-based systems. CONTACT: enis.afgan@unimelb.edu.au.

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RUbioSeq: a suite of parallelized pipelines to automate exome variation and bisulfite-seq analyses.

Publication Date: 2013 May 24 PMID: 23630175
Authors: Rubio-Camarillo, M. - Gomez-Lopez, G. - Fernandez, J. M. - Valencia, A. - Pisano, D. G.
Journal: Bioinformatics

MOTIVATION: RUbioSeq has been developed to facilitate the primary and secondary analysis of re-sequencing projects by providing an integrated software suite of parallelized pipelines to detect exome variants (single-nucleotide variants and copy number variations) and to perform bisulfite-seq analyses automatically. RUbioSeq's variant analysis results have been already validated and published. AVAILABILITY: http://rubioseq.sourceforge.net/. CONTACT: mrubioc@cnio.es.

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KGVDB: a population-based genomic map of CNVs tagged by SNPs in Koreans.

Publication Date: 2013 Jun 1 PMID: 23626002
Authors: Moon, S. - Jung, K. S. - Kim, Y. J. - Hwang, M. Y. - Han, K. - Lee, J. Y. - Park, K. - Kim, B. J.
Journal: Bioinformatics

SUMMARY: Despite a growing interest in a correlation between copy number variations (CNVs) and flanking single nucleotide polymorphisms, few databases provide such information. In particular, most information on CNV available so far was obtained in Caucasian and Yoruba populations, and little is known about CNV in Asian populations. This article presents a database that provides CNV regions tagged by single nucleotide polymorphisms in about 4700 Koreans, which were detected under strict quality control, manually curated and experimentally validated. AVAILABILITY: KGVDB is freely available for non-commercial use at http://biomi.cdc.go.kr/KGVDB. CONTACT: kbj6181@cdc.go.kr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites.

Publication Date: 2013 May 23 PMID: 23626001
Authors: Chen, X. - Qiu, J. D. - Shi, S. P. - Suo, S. B. - Huang, S. Y. - Liang, R. P.
Journal: Bioinformatics

MOTIVATION: Systematic dissection of the ubiquitylation proteome is emerging as an appealing but challenging research topic because of the significant roles ubiquitylation play not only in protein degradation but also in many other cellular functions. High-throughput experimental studies using mass spectrometry have identified many ubiquitylation sites, primarily from eukaryotes. However, the vast majority of ubiquitylation sites remain undiscovered, even in well-studied systems. Because mass spectrometry-based experimental approaches for identifying ubiquitylation events are costly, time-consuming and biased toward abundant proteins and proteotypic peptides, in silico prediction of ubiquitylation sites is a potentially useful alternative strategy for whole proteome annotation. Because of various limitations, current ubiquitylation site prediction tools were not well designed to comprehensively assess proteomes. RESULTS: We present a novel tool known as UbiProber, specifically designed for large-scale predictions of both general and species-specific ubiquitylation sites. We collected proteomics data for ubiquitylation from multiple species from several reliable sources and used them to train prediction models by a comprehensive machine-learning approach that integrates the information from key positions and key amino acid residues. Cross-validation tests reveal that UbiProber achieves some improvement over existing tools in predicting species-specific ubiquitylation sites. Moreover, independent tests show that UbiProber improves the areas under receiver operating characteristic curves by approximately 15% by using the Combined model. AVAILABILITY: The UbiProber server is freely available on the web at http://bioinfo.ncu.edu.cn/UbiProber.aspx. The software system of UbiProber can be downloaded at the same site. CONTACT: jdqiu@ncu.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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OCSANA: optimal combinations of interventions from network analysis.

Publication Date: 2013 Jun 15 PMID: 23626000
Authors: Vera-Licona, P. - Bonnet, E. - Barillot, E. - Zinovyev, A.
Journal: Bioinformatics

Targeted therapies interfering with specifically one protein activity are promising strategies in the treatment of diseases like cancer. However, accumulated empirical experience has shown that targeting multiple proteins in signaling networks involved in the disease is often necessary. Thus, one important problem in biomedical research is the design and prioritization of optimal combinations of interventions to repress a pathological behavior, while minimizing side-effects. OCSANA (optimal combinations of interventions from network analysis) is a new software designed to identify and prioritize optimal and minimal combinations of interventions to disrupt the paths between source nodes and target nodes. When specified by the user, OCSANA seeks to additionally minimize the side effects that a combination of interventions can cause on specified off-target nodes. With the crucial ability to cope with very large networks, OCSANA includes an exact solution and a novel selective enumeration approach for the combinatorial interventions' problem. AVAILABILITY: The latest version of OCSANA, implemented as a plugin for Cytoscape and distributed under LGPL license, is available together with source code at http://bioinfo.curie.fr/projects/ocsana. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: paola.vera-licona@curie.fr.

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NetworkTrail--a web service for identifying and visualizing deregulated subnetworks.

Publication Date: 2013 May 28 PMID: 23625999
Authors: Stockel, D. - Muller, O. - Kehl, T. - Gerasch, A. - Backes, C. - Rurainski, A. - Keller, A. - Kaufmann, M. - Lenhof, H. P.
Journal: Bioinformatics

SUMMARY: The deregulation of biochemical pathways plays a central role in many diseases like cancer or Parkinsons's disease. In silico tools for calculating these deregulated pathways may help to gain new insights into pathogenic mechanisms and may open novel avenues for therapy stratification in the sense of personalized medicine. Here, we present NetworkTrail, a web service for the detection of deregulated pathways and subgraphs in biological networks. NetworkTrail uses a state-of-the-art integer linear programming-based approach for this task and offers interfaces to the Biological Network Analyzer (BiNA) and Cytoscape Web for visualizing the resulting subnetworks. By providing an accessible interface to otherwise hard-to-use command line tools, the new web service enables non-experts to quickly and reliably carry out this type of network analyses.Availability and implementation: NetworkTrail is a JavaServer Pages-based web service. The algorithm for finding deregulated subnetworks has been implemented in C++. NetworkTrail is available at http://networktrail.bioinf.uni-sb.de/. CONTACT: dstoeckel@bioinf.uni-sb.de.

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HOMECAT: consensus homologs mapping for interspecific knowledge transfer and functional genomic data integration.

Publication Date: 2013 Jun 15 PMID: 23620364
Authors: Zorzan, S. - Lorenzetto, E. - Ettorre, M. - Pontelli, V. - Laudanna, C. - Buffelli, M.
Journal: Bioinformatics

MOTIVATION: Comparative studies are encouraged by the fast increase of data availability from the latest high-throughput techniques, in particular from functional genomic studies. Yet, the size of datasets, the challenge of complete orthologs findings and not last, the variety of identification formats, make information integration challenging. With HOMECAT, we aim to facilitate cross-species relationship identification and data mapping, by combining orthology predictions from several publicly available sources, a convenient interface for high-throughput data download and automatic identifier conversion into a Cytoscape plug-in, that provides both an integration with a large set of bioinformatics tools, as well as a user-friendly interface. AVAILABILITY: HOMECAT and the Supplementary Materials are freely available at http://www.cbmc.it/homecat/. CONTACT: simone.zorzan@univr.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Predicting the functional consequences of cancer-associated amino acid substitutions.

Publication Date: 2013 Jun 15 PMID: 23620363
Authors: Shihab, H. A. - Gough, J. - Cooper, D. N. - Day, I. N. - Gaunt, T. R.
Journal: Bioinformatics

MOTIVATION: The number of missense mutations being identified in cancer genomes has greatly increased as a consequence of technological advances and the reduced cost of whole-genome/whole-exome sequencing methods. However, a high proportion of the amino acid substitutions detected in cancer genomes have little or no effect on tumour progression (passenger mutations). Therefore, accurate automated methods capable of discriminating between driver (cancer-promoting) and passenger mutations are becoming increasingly important. In our previous work, we developed the Functional Analysis through Hidden Markov Models (FATHMM) software and, using a model weighted for inherited disease mutations, observed improved performances over alternative computational prediction algorithms. Here, we describe an adaptation of our original algorithm that incorporates a cancer-specific model to potentiate the functional analysis of driver mutations. RESULTS: The performance of our algorithm was evaluated using two separate benchmarks. In our analysis, we observed improved performances when distinguishing between driver mutations and other germ line variants (both disease-causing and putatively neutral mutations). In addition, when discriminating between somatic driver and passenger mutations, we observed performances comparable with the leading computational prediction algorithms: SPF-Cancer and TransFIC. Availability and implementation: A web-based implementation of our cancer-specific model, including a downloadable stand-alone package, is available at http://fathmm.biocompute.org.uk. CONTACT: fathmm@biocompute.org.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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RSVSim: an R/Bioconductor package for the simulation of structural variations.

Publication Date: 2013 May 23 PMID: 23620362
Authors: Bartenhagen, C. - Dugas, M.
Journal: Bioinformatics

SUMMARY: RSVSim is a tool for the simulation of deletions, insertions, inversions, tandem duplications and translocations of various sizes in any genome available as FASTA-file or data package in R. The structural variations can be generated randomly, based on user-supplied genomic coordinates or associated to various kinds of repeats. The package further comprises functions to estimate the distribution of structural variation sizes from real datasets. AVAILABILITY: RSVSim is implemented in R and available at http://www.bioconductor.org. A vignette with detailed descriptions of the functions and examples is included. CONTACT: christoph.bartenhagen@uni-muenster.de.

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Sharing and executing linked data queries in a collaborative environment.

Publication Date: 2013 May 22 PMID: 23620361
Authors: Garcia Godoy, M. J. - Lopez-Camacho, E. - Navas-Delgado, I. - Aldana-Montes, J. F.
Journal: Bioinformatics

MOTIVATION: Life Sciences have emerged as a key domain in the Linked Data community because of the diversity of data semantics and formats available through a great variety of databases and web technologies. Thus, it has been used as the perfect domain for applications in the web of data. Unfortunately, bioinformaticians are not exploiting the full potential of this already available technology, and experts in Life Sciences have real problems to discover, understand and devise how to take advantage of these interlinked (integrated) data. RESULTS: In this article, we present Bioqueries, a wiki-based portal that is aimed at community building around biological Linked Data. This tool has been designed to aid bioinformaticians in developing SPARQL queries to access biological databases exposed as Linked Data, and also to help biologists gain a deeper insight into the potential use of this technology. This public space offers several services and a collaborative infrastructure to stimulate the consumption of biological Linked Data and, therefore, contribute to implementing the benefits of the web of data in this domain. Bioqueries currently contains 215 query entries grouped by database and theme, 230 registered users and 44 end points that contain biological Resource Description Framework information. AVAILABILITY: The Bioqueries portal is freely accessible at http://bioqueries.uma.es. CONTACT: jfam@lcc.uma.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Shimmer: detection of genetic alterations in tumors using next-generation sequence data.

Publication Date: 2013 Jun 15 PMID: 23620360
Authors: Hansen, N. F. - Gartner, J. J. - Mei, L. - Samuels, Y. - Mullikin, J. C.
Journal: Bioinformatics

MOTIVATION: Extensive DNA sequencing of tumor and matched normal samples using exome and whole-genome sequencing technologies has enabled the discovery of recurrent genetic alterations in cancer cells, but variability in stromal contamination and subclonal heterogeneity still present a severe challenge to available detection algorithms. RESULTS: Here, we describe publicly available software, Shimmer, which accurately detects somatic single-nucleotide variants using statistical hypothesis testing with multiple testing correction. This program produces somatic single-nucleotide variant predictions with significantly higher sensitivity and accuracy than other available software when run on highly contaminated or heterogeneous samples, and it gives comparable sensitivity and accuracy when run on samples of high purity. AVAILABILITY: http://www.github.com/nhansen/Shimmer CONTACT: nhansen@mail.nih.gov SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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A novel web server predicts amino acid residue protection against hydrogen-deuterium exchange.

Publication Date: 2013 Jun 1 PMID: 23620358
Authors: Lobanov, M. Y. - Suvorina, M. Y. - Dovidchenko, N. V. - Sokolovskiy, I. V. - Surin, A. K. - Galzitskaya, O. V.
Journal: Bioinformatics

MOTIVATION: To clarify the relationship between structural elements and polypeptide chain mobility, a set of statistical analyses of structures is necessary. Because at present proteins with determined spatial structures are much less numerous than those with amino acid sequence known, it is important to be able to predict the extent of proton protection from hydrogen-deuterium (HD) exchange basing solely on the protein primary structure. RESULTS: Here we present a novel web server aimed to predict the degree of amino acid residue protection against HD exchange solely from the primary structure of the protein chain under study. On the basis of the amino acid sequence, the presented server offers the following three possibilities (predictors) for user's choice. First, prediction of the number of contacts occurring in this protein, which is shown to be helpful in estimating the number of protons protected against HD exchange (sensitivity 0.71). Second, probability of H-bonding in this protein, which is useful for finding the number of unprotected protons (specificity 0.71). The last is the use of an artificial predictor. Also, we report on mass spectrometry analysis of HD exchange that has been first applied to free amino acids. Its results showed a good agreement with theoretical data (number of protons) for 10 globular proteins (correlation coefficient 0.73). We pioneered in compiling two datasets of experimental HD exchange data for 35 proteins. AVAILABILITY: The H-Protection server is available for users at http://bioinfo.protres.ru/ogp/ CONTACT: ogalzit@vega.protres.ru SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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A support vector machine for identification of single-nucleotide polymorphisms from next-generation sequencing data.

Publication Date: 2013 Jun 1 PMID: 23620357
Authors: O'Fallon, B. D. - Wooderchak-Donahue, W. - Crockett, D. K.
Journal: Bioinformatics

MOTIVATION: Accurate determination of single-nucleotide polymorphisms (SNPs) from next-generation sequencing data is a significant challenge facing bioinformatics researchers. Most current methods use mechanistic models that assume nucleotides aligning to a given reference position are sampled from a binomial distribution. While such methods are sensitive, they are often unable to discriminate errors resulting from misaligned reads, sequencing errors or platform artifacts from true variants. RESULTS: To enable more accurate SNP calling, we developed an algorithm that uses a trained support vector machine (SVM) to determine variants from .BAM or .SAM formatted alignments of sequence reads. Our SVM-based implementation determines SNPs with significantly greater sensitivity and specificity than alternative platforms, including the UnifiedGenotyper included with the Genome Analysis Toolkit, samtools and FreeBayes. In addition, the quality scores produced by our implementation more accurately reflect the likelihood that a variant is real when compared with those produced by the Genome Analysis Toolkit. While results depend on the model used, the implementation includes tools to easily build new models and refine existing models with additional training data. AVAILABILITY: Source code and executables are available from github.com/brendanofallon/SNPSVM/ CONTACT: brendan.d.ofallon@aruplab.com or david.crockett@aruplab.com.

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Structural RNA alignment by multi-objective optimization.

Publication Date: 2013 May 24 PMID: 23620356
Authors: Schnattinger, T. - Schoning, U. - Kestler, H. A.
Journal: Bioinformatics

MOTIVATION: The calculation of reliable alignments for structured RNA is still considered as an open problem. One approach is the incorporation of secondary structure information into the optimization criteria by using a weighted sum of sequence and structure components as an objective function. As it is not clear how to choose the weighting parameters, we use multi-objective optimization to calculate a set of Pareto-optimal RNA sequence-structure alignments. The solutions in this set then represent all possible trade-offs between the different objectives, independent of any previous weighting. RESULTS: We present a practical multi-objective dynamic programming algorithm, which is a new method for the calculation of the set of Pareto-optimal solutions to the pairwise RNA sequence-structure alignment problem. In selected examples, we show the usefulness of this approach, and its advantages over state-of-the-art single-objective algorithms.Availability and implementation: The source code of our software (ISO C++11) is freely available at http://sysbio.uni-ulm.de/?Software and is licensed under the GNU GPLv3. CONTACT: hans.kestler@uni-ulm.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences.

Publication Date: 2013 Jun 1 PMID: 23616439
Authors: Kalkatawi, M. - Rangkuti, F. - Schramm, M. - Jankovic, B. R. - Kamau, A. - Chowdhary, R. - Archer, J. A. - Bajic, V. B.
Journal: Bioinformatics

CONTACT: vladimir.bajic@kaust.edu.sa SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Systematic tracking of dysregulated modules identifies novel genes in cancer.

Publication Date: 2013 Jun 15 PMID: 23613489
Authors: Srihari, S. - Ragan, M. A.
Journal: Bioinformatics

MOTIVATION: Deciphering the modus operandi of dysregulated cellular mechanisms in cancer is critical to implicate novel cancer genes and develop effective anti-cancer therapies. Fundamental to this is meticulous tracking of the behavior of core modules, including complexes and pathways across specific conditions in cancer. RESULTS: Here, we performed a straightforward yet systematic identification and comparison of modules across pancreatic normal and cancer tissue conditions by integrating PPI, gene-expression and mutation data. Our analysis revealed interesting change-patterns in gene composition and expression correlation particularly affecting modules responsible for genome stability. Although in most cases these changes indicated impairment of essential functions (e.g. of DNA damage repair), in several other cases we noticed strengthening of modules possibly abetting cancer. Some of these compensatory modules showed switches in transcription regulation and recruitment of tumor inducers (e.g. SOX2 through overexpression). In-depth analysis revealed novel genes in pancreatic cancer, which showed susceptibility to copy-number alterations (e.g. for USP15 in 17 of 67 cases), supported by literature evidence for their involvement in other tumors (e.g. USP15 in glioblastoma). Two of the identified genes, YWHAE and DISC1, further supported the nexus between neural genes and pancreatic carcinogenesis. Extension of this assessment to BRCA1 and BRCA2 breast tumors showed specific differences even across the two sub-types and revealed novel genes involved therein (e.g. TRIM5 and NCOA6). AVAILABILITY: Our software CONTOURv1 is available at: http://bioinformatics.org.au/tools-data/. CONTACT: m.ragan@uq.edu.au SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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CellAging: a tool to study segregation and partitioning in division in cell lineages of Escherichia coli.

Publication Date: 2013 May 18 PMID: 23613488
Authors: Hakkinen, A. - Muthukrishnan, A. B. - Mora, A. - Fonseca, J. M. - Ribeiro, A. S.
Journal: Bioinformatics

MOTIVATION: Cell division in Escherichia coli is morphologically symmetric. However, as unwanted protein aggregates are segregated to the cell poles and, after divisions, accumulate at older poles, generate asymmetries in sister cells' vitality. Novel single-molecule detection techniques allow observing aging-related processes in vivo, over multiple generations, informing on the underlying mechanisms. RESULTS: CellAging is a tool to automatically extract information on polar segregation and partitioning in division of aggregates in E.coli, and on cellular vitality. From time-lapse, parallel brightfield and fluorescence microscopy images, it performs cell segmentation, alignment of brightfield and fluorescence images, lineage construction and pole age determination, and it computes aging-related features. We exemplify its use by analyzing spatial distributions of fluorescent protein aggregates from images of cells across generations. AVAILABILITY: CellAging, instructions and an example are available at http://www.cs.tut.fi/%7esanchesr/cellaging/. CONTACT: andre.ribeiro@tut.fi SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters.

Publication Date: 2013 May 18 PMID: 23613487
Authors: Jonsson, H. - Ginolhac, A. - Schubert, M. - Johnson, P. L. - Orlando, L.
Journal: Bioinformatics

MOTIVATION: Ancient DNA (aDNA) molecules in fossilized bones and teeth, coprolites, sediments, mummified specimens and museum collections represent fantastic sources of information for evolutionary biologists, revealing the agents of past epidemics and the dynamics of past populations. However, the analysis of aDNA generally faces two major issues. Firstly, sequences consist of a mixture of endogenous and various exogenous backgrounds, mostly microbial. Secondly, high nucleotide misincorporation rates can be observed as a result of severe post-mortem DNA damage. Such misincorporation patterns are instrumental to authenticate ancient sequences versus modern contaminants. We recently developed the user-friendly mapDamage package that identifies such patterns from next-generation sequencing (NGS) sequence datasets. The absence of formal statistical modeling of the DNA damage process, however, precluded rigorous quantitative comparisons across samples. RESULTS: Here, we describe mapDamage 2.0 that extends the original features of mapDamage by incorporating a statistical model of DNA damage. Assuming that damage events depend only on sequencing position and post-mortem deamination, our Bayesian statistical framework provides estimates of four key features of aDNA molecules: the average length of overhangs (lambda), nick frequency (nu) and cytosine deamination rates in both double-stranded regions () and overhangs (). Our model enables rescaling base quality scores according to their probability of being damaged. mapDamage 2.0 handles NGS datasets with ease and is compatible with a wide range of DNA library protocols. AVAILABILITY: mapDamage 2.0 is available at ginolhac.github.io/mapDamage/ as a Python package and documentation is maintained at the Centre for GeoGenetics Web site (geogenetics.ku.dk/publications/mapdamage2.0/). CONTACT: jonsson.hakon@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Mendel: the Swiss army knife of genetic analysis programs.

Publication Date: 2013 Jun 15 PMID: 23610370
Authors: Lange, K. - Papp, J. C. - Sinsheimer, J. S. - Sripracha, R. - Zhou, H. - Sobel, E. M.
Journal: Bioinformatics

SUMMARY: Mendel is one of the few statistical genetics packages that provide a full spectrum of gene mapping methods, ranging from parametric linkage in large pedigrees to genome-wide association with rare variants. Our latest additions to Mendel anticipate and respond to the needs of the genetics community. Compared with earlier versions, Mendel is faster and easier to use and has a wider range of applications. Supported platforms include Linux, MacOS and Windows. Availability: Free from www.genetics.ucla.edu/software/mendel CONTACT: klange@ucla.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Automated annotation and quantification of glycans using liquid chromatography-mass spectrometry.

Publication Date: 2013 May 28 PMID: 23610369
Authors: Yu, C. Y. - Mayampurath, A. - Hu, Y. - Zhou, S. - Mechref, Y. - Tang, H.
Journal: Bioinformatics

SUMMARY: As a common post-translational modification, protein glycosylation plays an important role in many biological processes, and it is known to be associated with human diseases. Mass spectrometry (MS)-based glycomic profiling techniques have been developed to measure the abundances of glycans in complex biological samples and applied to the discovery of putative glycan biomarkers. To automate the annotation of glycomic profiles in the liquid chromatography-MS (LC-MS) data, we present here a user-friendly software tool, MultiGlycan, implemented in C# on Windows systems. We tested MultiGlycan by using several glycomic profiling datasets acquired using LC-MS under different preparations and show that MultiGlycan executes fast and generates robust and reliable results. AVAILABILITY: MultiGlycan can be freely downloaded at http://darwin.informatics.indiana.edu/MultiGlycan/. CONTACT: chuyu@indiana.edu or hatang@indiana.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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A multi-layer inference approach to reconstruct condition-specific genes and their regulation.

Publication Date: 2013 Jun 15 PMID: 23610368
Authors: Wu, M. - Liu, L. - Hijazi, H. - Chan, C.
Journal: Bioinformatics

An important topic in systems biology is the reverse engineering of regulatory mechanisms through reconstruction of context-dependent gene networks. A major challenge is to identify the genes and the regulations specific to a condition or phenotype, given that regulatory processes are highly connected such that a specific response is typically accompanied by numerous collateral effects. In this study, we design a multi-layer approach that is able to reconstruct condition-specific genes and their regulation through an integrative analysis of large-scale information of gene expression, protein interaction and transcriptional regulation (transcription factor-target gene relationships). We establish the accuracy of our methodology against synthetic datasets, as well as a yeast dataset. We then extend the framework to the application of higher eukaryotic systems, including human breast cancer and Arabidopsis thaliana cold acclimation. Our study identified TACSTD2 (TROP2) as a target gene for human breast cancer and discovered its regulation by transcription factors CREB, as well as NFkB. We also predict KIF2C is a target gene for ER-/HER2- breast cancer and is positively regulated by E2F1. The predictions were further confirmed through experimental studies. AVAILABILITY: The implementation and detailed protocol of the layer approach is available at http://www.egr.msu.edu/changroup/Protocols/Three-layer%20approach%20to%20reconstr uct%20condition.html. CONTACT: krischan@egr.msu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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ELOPER: elongation of paired-end reads as a pre-processing tool for improved de novo genome assembly.

Publication Date: 2013 Jun 1 PMID: 23603334
Authors: Silver, D. H. - Ben-Elazar, S. - Bogoslavsky, A. - Yanai, I.
Journal: Bioinformatics

MOTIVATION: Paired-end sequencing resulting in gapped short reads is commonly used for de novo genome assembly. Assembly methods use paired-end sequences in a two-step process, first treating each read-end independently, only later invoking the pairing to join the contiguous assemblies (contigs) into gapped scaffolds. Here, we present ELOPER, a pre-processing tool for pair-end sequences that produces a better read library for assembly programs. RESULTS: ELOPER proceeds by simultaneously considering both ends of paired reads generating elongated reads. We show that ELOPER theoretically doubles read-lengths while halving the number of reads. We provide evidence that pre-processing read libraries using ELOPER leads to considerably improved assemblies as predicted from the Lander-Waterman model. AVAILABILITY: http://sourceforge.net/projects/eloper. CONTACT: yanai@technion.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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rRNA:mRNA pairing alters the length and the symmetry of mRNA-protected fragments in ribosome profiling experiments.

Publication Date: 2013 Jun 15 PMID: 23603333
Authors: O'Connor, P. B. - Li, G. W. - Weissman, J. S. - Atkins, J. F. - Baranov, P. V.
Journal: Bioinformatics

MOTIVATION: Ribosome profiling is a new technique that allows monitoring locations of translating ribosomes on mRNA at a whole transcriptome level. A recent ribosome profiling study demonstrated that internal Shine-Dalgarno (SD) sequences have a major global effect on translation rates in bacteria: ribosomes pause at SD sites in mRNA. Therefore, it is important to understand how SD sites effect mRNA movement through the ribosome and generation of ribosome footprints. RESULTS: Here, we provide evidence that in addition to pausing effect, internal SD sequences induce a caterpillar-like movement of mRNA through the ribosome cavity. Once an SD site binds to the ribosome, it remains attached to it while the ribosome decodes a few subsequent codons. This leads to asymmetric progressive elongation of ribosome footprints at the 3'-end. It is likely that internal SD sequences induce a pause not on a single, but on several adjacent codons. This finding is important for our understanding of mRNA movement through the ribosome and also should facilitate interpretation of ribosome profiling data. CONTACT: brave.oval.pan@gmail.com.

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APP2: automatic tracing of 3D neuron morphology based on hierarchical pruning of a gray-weighted image distance-tree.

Publication Date: 2013 Jun 1 PMID: 23603332
Authors: Xiao, H. - Peng, H.
Journal: Bioinformatics

MOTIVATION: Tracing of neuron morphology is an essential technique in computational neuroscience. However, despite a number of existing methods, few open-source techniques are completely or sufficiently automated and at the same time are able to generate robust results for real 3D microscopy images. RESULTS: We developed all-path-pruning 2.0 (APP2) for 3D neuron tracing. The most important idea is to prune an initial reconstruction tree of a neuron's morphology using a long-segment-first hierarchical procedure instead of the original termini-first-search process in APP. To further enhance the robustness of APP2, we compute the distance transform of all image voxels directly for a gray-scale image, without the need to binarize the image before invoking the conventional distance transform. We also design a fast-marching algorithm-based method to compute the initial reconstruction trees without pre-computing a large graph. This method allows us to trace large images. We bench-tested APP2 on approximately 700 3D microscopic images and found that APP2 can generate more satisfactory results in most cases than several previous methods. AVAILABILITY: The software has been implemented as an open-source Vaa3D plugin. The source code is available in the Vaa3D code repository http://vaa3d.org. CONTACT: hanchuanp@alleninstitute.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics from thermal fluctuation data.

Publication Date: 2013 Jun 15 PMID: 23599504
Authors: Ju, L. - Wang, Y. D. - Hung, Y. - Wu, C. F. - Zhu, C.
Journal: Bioinformatics

MOTIVATION: Abrupt reduction/resumption of thermal fluctuations of a force probe has been used to identify association/dissociation events of protein-ligand bonds. We show that off-rate of molecular dissociation can be estimated by the analysis of the bond lifetime, while the on-rate of molecular association can be estimated by the analysis of the waiting time between two neighboring bond events. However, the analysis relies heavily on subjective judgments and is time-consuming. To automate the process of mapping out bond events from thermal fluctuation data, we develop a hidden Markov model (HMM)-based method. RESULTS: The HMM method represents the bond state by a hidden variable with two values: bound and unbound. The bond association/dissociation is visualized and pinpointed. We apply the method to analyze a key receptor-ligand interaction in the early stage of hemostasis and thrombosis: the von Willebrand factor (VWF) binding to platelet glycoprotein Ibalpha (GPIbalpha). The numbers of bond lifetime and waiting time events estimated by the HMM are much more than those estimated by a descriptive statistical method from the same set of raw data. The kinetic parameters estimated by the HMM are in excellent agreement with those by a descriptive statistical analysis, but have much smaller errors for both wild-type and two mutant VWF-A1 domains. Thus, the computerized analysis allows us to speed up the analysis and improve the quality of estimates of receptor-ligand binding kinetics. CONTACT: jeffwu@isye.gatech.edu or cheng.zhu@bme.gatech.edu.

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A powerful and efficient set test for genetic markers that handles confounders.

Publication Date: 2013 Jun 15 PMID: 23599503
Authors: Listgarten, J. - Lippert, C. - Kang, E. Y. - Xiang, J. - Kadie, C. M. - Heckerman, D.
Journal: Bioinformatics

MOTIVATION: Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the burden of multiple hypothesis testing. Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power. RESULTS: We introduce a new approach for set tests that handles confounders. Our model is based on the linear mixed model and uses two random effects-one to capture the set association signal and one to capture confounders. We also introduce a computational speedup for two random-effects models that makes this approach feasible even for extremely large cohorts. Using this model with both the likelihood ratio test and score test, we find that the former yields more power while controlling type I error. Application of our approach to richly structured Genetic Analysis Workshop 14 data demonstrates that our method successfully corrects for population structure and family relatedness, whereas application of our method to a 15 000 individual Crohn's disease case-control cohort demonstrates that it additionally recovers genes not recoverable by univariate analysis. AVAILABILITY: A Python-based library implementing our approach is available at http://mscompbio.codeplex.com. CONTACT: jennl@microsoft.com or lippert@microsoft.com or heckerma@microsoft.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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INstruct: a database of high-quality 3D structurally resolved protein interactome networks.

Publication Date: 2013 May 17 PMID: 23599502
Authors: Meyer, M. J. - Das, J. - Wang, X. - Yu, H.
Journal: Bioinformatics

SUMMARY: INstruct is a database of high-quality, 3D, structurally resolved protein interactome networks in human and six model organisms. INstruct combines the scale of available high-quality binary protein interaction data with the specificity of atomic-resolution structural information derived from co-crystal evidence using a tested interaction interface inference method. Its web interface is designed to allow for flexible search based on standard and organism-specific protein and gene-naming conventions, visualization of protein architecture highlighting interaction interfaces and viewing and downloading custom 3D structurally resolved interactome datasets. AVAILABILITY: INstruct is freely available on the web at http://instruct.yulab.org with all major browsers supported. CONTACT: haiyuan.yu@cornell.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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CellH5: a format for data exchange in high-content screening.

Publication Date: 2013 May 8 PMID: 23595665
Authors: Sommer, C. - Held, M. - Fischer, B. - Huber, W. - Gerlich, D. W.
Journal: Bioinformatics

SUMMARY: High-throughput microscopy data require a diversity of analytical approaches. However, the construction of workflows that use algorithms from different software packages is difficult owing to a lack of interoperability. To overcome this limitation, we present CellH5, an HDF5 data format for cell-based assays in high-throughput microscopy, which stores high-dimensional image data along with inter-object relations in graphs. CellH5Browser, an interactive gallery image browser, demonstrates the versatility and performance of the file format on live imaging data of dividing human cells. CellH5 provides new opportunities for integrated data analysis by multiple software platforms. AVAILABILITY: Source code is freely available at www.github.com/cellh5 under the GPL license and at www.bioconductor.org/packages/release/bioc/html/rhdf5.html under the Artistic-2.0 license. Demo datasets and the CellH5Browser are available at www.cellh5.org. A Fiji importer for cellh5 will be released soon. CONTACT: daniel.gerlich@imba.oeaw.ac.at or christoph.sommer@imba.oeaw.ac.at SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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NetworkPrioritizer: a versatile tool for network-based prioritization of candidate disease genes or other molecules.

Publication Date: 2013 Jun 1 PMID: 23595661
Authors: Kacprowski, T. - Doncheva, N. T. - Albrecht, M.
Journal: Bioinformatics

SUMMARY: The prioritization of candidate disease genes is often based on integrated datasets and their network representation with genes as nodes connected by edges for biological relationships. However, the majority of prioritization methods does not allow for a straightforward integration of the user's own input data. Therefore, we developed the Cytoscape plugin NetworkPrioritizer that particularly supports the integrative network-based prioritization of candidate disease genes or other molecules. Our versatile software tool computes a number of important centrality measures to rank nodes based on their relevance for network connectivity and provides different methods to aggregate and compare rankings. AVAILABILITY: NetworkPrioritizer and the online documentation are freely available at http://www.networkprioritizer.de. CONTACT: mario.albrecht@mpi-inf.mpg.de.

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Learning gene network structure from time laps cell imaging in RNAi Knock downs.

Publication Date: 2013 May 8 PMID: 23595660
Authors: Failmezger, H. - Praveen, P. - Tresch, A. - Frohlich, H.
Journal: Bioinformatics

MOTIVATION: As RNA interference is becoming a standard method for targeted gene perturbation, computational approaches to reverse engineer parts of biological networks based on measurable effects of RNAi become increasingly relevant. The vast majority of these methods use gene expression data, but little attention has been paid so far to other data types.Results: Here we present a method, which can infer gene networks from high-dimensional phenotypic perturbation effects on single cells recorded by time-lapse microscopy. We use data from the Mitocheck project to extract multiple shape, intensity and texture features at each frame. Features from different cells and movies are then aligned along the cell cycle time. Subsequently we use Dynamic Nested Effects Models (dynoNEMs) to estimate parts of the network structure between perturbed genes via a Markov Chain Monte Carlo approach. Our simulation results indicate a high reconstruction quality of this method. A reconstruction based on 22 gene knock downs yielded a network, where all edges could be explained via the biological literature.Availability: The implementation of dynoNEMs is part of the Bioconductor R-package nem. CONTACT: frohlich@bit.uni-bonn.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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UPDtool: a tool for detection of iso- and heterodisomy in parent-child trios using SNP microarrays.

Publication Date: 2013 May 6 PMID: 23589652
Authors: Schroeder, C. - Sturm, M. - Dufke, A. - Mau-Holzmann, U. - Eggermann, T. - Poths, S. - Riess, O. - Bonin, M.
Journal: Bioinformatics

SUMMARY: UPDtool is a computational tool for detection and classification of uniparental disomy (UPD) in trio SNP-microarray experiments. UPDs are rare events of chromosomal malsegregation and describe the condition of two homologous chromosomes or homologous chromosomal segments that were inherited from one parent. The occurrence of UPD can be of major clinical relevance. Though high-throughput molecular screening techniques are widely used, detection of UPDs and especially the subclassification remains complex. We developed UPDtool to detect and classify UPDs from SNP microarray data of parent-child trios. The algorithm was tested using five positive controls including both iso- and heterodisomic segmental UPDs and 30 trios from the HapMap project as negative controls. With UPDtool, we were able to correctly identify all occurrences of non-mosaic UPD within our positive controls, whereas no occurrence of UPD was found within our negative controls. In addition, the chromosomal breakage points could be determined more precisely than by microsatellite analysis. Our results were compared with both the gold standard, microsatellite analysis and SNPtrio, another program available for UPD detection. UPDtool is platform independent, light weight and flexible. Because of its simple input format, UPDtool may also be used with other high-throughput technologies (e.g. next-generation sequencing).Availability and implementation: UPDtool executables, documentation and examples can be downloaded from http://www.uni-tuebingen.de/uni/thk/de/f-genomik-software.html. CONTACT: christopher.schroeder@med.uni-tuebingen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Novel algorithms and the benefits of comparative validation.

Publication Date: 2013 May 10 PMID: 23589651
Authors: Smith, R. - Ventura, D. - Prince, J. T.
Journal: Bioinformatics

CONTACT: 2robsmith@gmail.com.

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Exome-based analysis for RNA epigenome sequencing data.

Publication Date: 2013 May 10 PMID: 23589649
Authors: Meng, J. - Cui, X. - Rao, M. K. - Chen, Y. - Huang, Y.
Journal: Bioinformatics

MOTIVATION: Fragmented RNA immunoprecipitation combined with RNA sequencing enabled the unbiased study of RNA epigenome at a near single-base resolution; however, unique features of this new type of data call for novel computational techniques. RESULT: Through examining the connections of RNA epigenome sequencing data with two well-studied data types, ChIP-Seq and RNA-Seq, we unveiled the salient characteristics of this new data type. The computational strategies were discussed accordingly, and a novel data processing pipeline was proposed that combines several existing tools with a newly developed exome-based approach 'exomePeak' for detecting, representing and visualizing the post-transcriptional RNA modification sites on the transcriptome. AVAILABILITY: The MATLAB package 'exomePeak' and additional details are available at http://compgenomics.utsa.edu/exomePeak/. CONTACT: yufei.huang@utsa.edu or jmeng@mit.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Biographer: web-based editing and rendering of SBGN compliant biochemical networks.

Publication Date: 2013 Jun 1 PMID: 23574737
Authors: Krause, F. - Schulz, M. - Ripkens, B. - Flottmann, M. - Krantz, M. - Klipp, E. - Handorf, T.
Journal: Bioinformatics

MOTIVATION: The rapid accumulation of knowledge in the field of Systems Biology during the past years requires advanced, but simple-to-use, methods for the visualization of information in a structured and easily comprehensible manner. RESULTS: We have developed biographer, a web-based renderer and editor for reaction networks, which can be integrated as a library into tools dealing with network-related information. Our software enables visualizations based on the emerging standard Systems Biology Graphical Notation. It is able to import networks encoded in various formats such as SBML, SBGN-ML and jSBGN, a custom lightweight exchange format. The core package is implemented in HTML5, CSS and JavaScript and can be used within any kind of web-based project. It features interactive graph-editing tools and automatic graph layout algorithms. In addition, we provide a standalone graph editor and a web server, which contains enhanced features like web services for the import and export of models and visualizations in different formats. AVAILABILITY: The biographer tool can be used at and downloaded from the web page http://biographer.biologie.hu-berlin.de/. The different software packages, including a server-indepenent version as well as a web server for Windows and Linux based systems, are available at http://code.google.com/p/biographer/ under the open-source license LGPL. CONTACT: edda.klipp@biologie.hu-berlin.de or handorf@physik.hu-berlin.de.

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OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks.

Publication Date: 2013 Jun 1 PMID: 23574736
Authors: Lim, N. - Senbabaoglu, Y. - Michailidis, G. - d'Alche-Buc, F.
Journal: Bioinformatics

MOTIVATION: Reverse engineering of gene regulatory networks remains a central challenge in computational systems biology, despite recent advances facilitated by benchmark in silico challenges that have aided in calibrating their performance. A number of approaches using either perturbation (knock-out) or wild-type time-series data have appeared in the literature addressing this problem, with the latter using linear temporal models. Nonlinear dynamical models are particularly appropriate for this inference task, given the generation mechanism of the time-series data. In this study, we introduce a novel nonlinear autoregressive model based on operator-valued kernels that simultaneously learns the model parameters, as well as the network structure. RESULTS: A flexible boosting algorithm (OKVAR-Boost) that shares features from L2-boosting and randomization-based algorithms is developed to perform the tasks of parameter learning and network inference for the proposed model. Specifically, at each boosting iteration, a regularized Operator-valued Kernel-based Vector AutoRegressive model (OKVAR) is trained on a random subnetwork. The final model consists of an ensemble of such models. The empirical estimation of the ensemble model's Jacobian matrix provides an estimation of the network structure. The performance of the proposed algorithm is first evaluated on a number of benchmark datasets from the DREAM3 challenge and then on real datasets related to the In vivo Reverse-Engineering and Modeling Assessment (IRMA) and T-cell networks. The high-quality results obtained strongly indicate that it outperforms existing approaches. AVAILABILITY: The OKVAR-Boost Matlab code is available as the archive: http://amis-group.fr/sourcecode-okvar-boost/OKVARBoost-v1.0.zip. CONTACT: florence.dalche@ibisc.univ-evry.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Measuring gene functional similarity based on group-wise comparison of GO terms.

Publication Date: 2013 Jun 1 PMID: 23572412
Authors: Teng, Z. - Guo, M. - Liu, X. - Dai, Q. - Wang, C. - Xuan, P.
Journal: Bioinformatics

MOTIVATION: Compared with sequence and structure similarity, functional similarity is more informative for understanding the biological roles and functions of genes. Many important applications in computational molecular biology require functional similarity, such as gene clustering, protein function prediction, protein interaction evaluation and disease gene prioritization. Gene Ontology (GO) is now widely used as the basis for measuring gene functional similarity. Some existing methods combined semantic similarity scores of single term pairs to estimate gene functional similarity, whereas others compared terms in groups to measure it. However, these methods may make error-prone judgments about gene functional similarity. It remains a challenge that measuring gene functional similarity reliably. RESULT: We propose a novel method called SORA to measure gene functional similarity in GO context. First of all, SORA computes the information content (IC) of a term making use of semantic specificity and coverage. Second, SORA measures the IC of a term set by means of combining inherited and extended IC of the terms based on the structure of GO. Finally, SORA estimates gene functional similarity using the IC overlap ratio of term sets. SORA is evaluated against five state-of-the-art methods in the file on the public platform for collaborative evaluation of GO-based semantic similarity measure. The carefully comparisons show SORA is superior to other methods in general. Further analysis suggests that it primarily benefits from the structure of GO, which implies expressive information about gene function. SORA offers an effective and reliable way to compare gene function. AVAILABILITY: The web service of SORA is freely available at http://nclab.hit.edu.cn/SORA/. CONTACT: maozuguo@hit.edu.cn.

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Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation.

Publication Date: 2013 Jun 1 PMID: 23572411
Authors: Pasaniuc, B. - Sankararaman, S. - Torgerson, D. G. - Gignoux, C. - Zaitlen, N. - Eng, C. - Rodriguez-Cintron, W. - Chapela, R. - Ford, J. G. - Avila, P. C. - Rodriguez-Santana, J. - Chen, G. K. - Le Marchand, L. - Henderson, B. - Reich, D. - Haiman, C. A. - Gonzalez Burchard, E. - Halperin, E.
Journal: Bioinformatics

MOTIVATION: Local ancestry analysis of genotype data from recently admixed populations (e.g. Latinos, African Americans) provides key insights into population history and disease genetics. Although methods for local ancestry inference have been extensively validated in simulations (under many unrealistic assumptions), no empirical study of local ancestry accuracy in Latinos exists to date. Hence, interpreting findings that rely on local ancestry in Latinos is challenging. RESULTS: Here, we use 489 nuclear families from the mainland USA, Puerto Rico and Mexico in conjunction with 3204 unrelated Latinos from the Multiethnic Cohort study to provide the first empirical characterization of local ancestry inference accuracy in Latinos. Our approach for identifying errors does not rely on simulations but on the observation that local ancestry in families follows Mendelian inheritance. We measure the rate of local ancestry assignments that lead to Mendelian inconsistencies in local ancestry in trios (MILANC), which provides a lower bound on errors in the local ancestry estimates. We show that MILANC rates observed in simulations underestimate the rate observed in real data, and that MILANC varies substantially across the genome. Second, across a wide range of methods, we observe that loci with large deviations in local ancestry also show enrichment in MILANC rates. Therefore, local ancestry estimates at such loci should be interpreted with caution. Finally, we reconstruct ancestral haplotype panels to be used as reference panels in local ancestry inference and show that ancestry inference is significantly improved by incoroprating these reference panels. Availability and implementation: We provide the reconstructed reference panels together with the maps of MILANC rates as a public resource for researchers analyzing local ancestry in Latinos at http://bogdanlab.pathology.ucla.edu. CONTACT: bpasaniuc@mednet.ucla.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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MonaLisa--visualization and analysis of functional modules in biochemical networks.

Publication Date: 2013 Jun 1 PMID: 23564846
Authors: Einloft, J. - Ackermann, J. - Nothen, J. - Koch, I.
Journal: Bioinformatics

SUMMARY: Structural modeling of biochemical networks enables qualitative as well as quantitative analysis of those networks. Automated network decomposition into functional modules is a crucial point in network analysis. Although there exist approaches for the analysis of networks, there is no open source tool available that combines editing, visualization and the computation of steady-state functional modules. We introduce a new tool called MonaLisa, which combines computation and visualization of functional modules as well as an editor for biochemical Petri nets. The analysis techniques allow for network decomposition into functional modules, for example t-invariants (elementary modes), maximal common transition sets, minimal cut sets and t-clusters. The graphical user interface provides various functionalities to construct and modify networks as well as to visualize the results of the analysis. Availability and implementation: MonaLisa is licensed under the Artistic License 2.0. It is freely available at http://www.bioinformatik.uni-frankfurt.de/software.html. MonaLisa requires at least Java 6 and runs under Linux, Microsoft Windows and Mac OS. CONTACT: ina.koch@bioinformatik.uni-frankfurt.de.

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Active learning-based information structure analysis of full scientific articles and two applications for biomedical literature review.

Publication Date: 2013 Jun 1 PMID: 23564844
Authors: Guo, Y. - Silins, I. - Stenius, U. - Korhonen, A.
Journal: Bioinformatics

MOTIVATION: Techniques that are capable of automatically analyzing the information structure of scientific articles could be highly useful for improving information access to biomedical literature. However, most existing approaches rely on supervised machine learning (ML) and substantial labeled data that are expensive to develop and apply to different sub-fields of biomedicine. Recent research shows that minimal supervision is sufficient for fairly accurate information structure analysis of biomedical abstracts. However, is it realistic for full articles given their high linguistic and informational complexity? We introduce and release a novel corpus of 50 biomedical articles annotated according to the Argumentative Zoning (AZ) scheme, and investigate active learning with one of the most widely used ML models-Support Vector Machines (SVM)-on this corpus. Additionally, we introduce two novel applications that use AZ to support real-life literature review in biomedicine via question answering and summarization. RESULTS: We show that active learning with SVM trained on 500 labeled sentences (6% of the corpus) performs surprisingly well with the accuracy of 82%, just 2% lower than fully supervised learning. In our question answering task, biomedical researchers find relevant information significantly faster from AZ-annotated than unannotated articles. In the summarization task, sentences extracted from particular zones are significantly more similar to gold standard summaries than those extracted from particular sections of full articles. These results demonstrate that active learning of full articles' information structure is indeed realistic and the accuracy is high enough to support real-life literature review in biomedicine. AVAILABILITY: The annotated corpus, our AZ classifier and the two novel applications are available at http://www.cl.cam.ac.uk/ approximately yg244/12bioinfo.html. CONTACT: yg244@cam.ac.uk.

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LibSBMLSim: a reference implementation of fully functional SBML simulator.

Publication Date: 2013 Jun 1 PMID: 23564843
Authors: Takizawa, H. - Nakamura, K. - Tabira, A. - Chikahara, Y. - Matsui, T. - Hiroi, N. - Funahashi, A.
Journal: Bioinformatics

MOTIVATION: The Systems Biology Markup Language (SBML) is currently supported by >230 software tools, among which 160 support numerical integration of ordinary differential equation (ODE) models. Although SBML is a widely accepted standard within this field, there is still no language-neutral library that supports all features of SBML for simulating ODE models. Therefore, a demand exists for a simple portable implementation of a numerical integrator that supports SBML to enhance the development of a computational platform for systems biology. RESULTS: We implemented a library called libSBMLSim, which supports all the features of SBML and confirmed that the library passes all tests in the SBML test suite including those for SBML Events, AlgebraicRules, 'fast' attribute on Reactions and Delay. LibSBMLSim is implemented in the C programming language and does not depend on any third-party library except libSBML, which is a library to handle SBML documents. For the numerical integrator, both explicit and implicit methods are written from scratch to support all the functionality of SBML features in a straightforward implementation. We succeeded in implementing libSBMLSim as a platform-independent library that can run on most common operating systems (Windows, MacOSX and Linux) and also provides several language bindings (Java, C#, Python and Ruby). AVAILABILITY: The source code of libSBMLSim is available from http://fun.bio.keio.ac.jp/software/libsbmlsim/. LibSBMLSim is distributed under the terms of LGPL. CONTACT: funa@bio.keio.ac.jp SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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tmVar: a text mining approach for extracting sequence variants in biomedical literature.

Publication Date: 2013 Jun 1 PMID: 23564842
Authors: Wei, C. H. - Harris, B. R. - Kao, H. Y. - Lu, Z.
Journal: Bioinformatics

MOTIVATION: Text-mining mutation information from the literature becomes a critical part of the bioinformatics approach for the analysis and interpretation of sequence variations in complex diseases in the post-genomic era. It has also been used for assisting the creation of disease-related mutation databases. Most of existing approaches are rule-based and focus on limited types of sequence variations, such as protein point mutations. Thus, extending their extraction scope requires significant manual efforts in examining new instances and developing corresponding rules. As such, new automatic approaches are greatly needed for extracting different kinds of mutations with high accuracy. RESULTS: Here, we report tmVar, a text-mining approach based on conditional random field (CRF) for extracting a wide range of sequence variants described at protein, DNA and RNA levels according to a standard nomenclature developed by the Human Genome Variation Society. By doing so, we cover several important types of mutations that were not considered in past studies. Using a novel CRF label model and feature set, our method achieves higher performance than a state-of-the-art method on both our corpus (91.4 versus 78.1% in F-measure) and their own gold standard (93.9 versus 89.4% in F-measure). These results suggest that tmVar is a high-performance method for mutation extraction from biomedical literature. AVAILABILITY: tmVar software and its corpus of 500 manually curated abstracts are available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/pub/tmVar. CONTACT: zhiyong.lu@nih.gov.

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Detecting regulatory gene-environment interactions with unmeasured environmental factors.

Publication Date: 2013 Jun 1 PMID: 23559640
Authors: Fusi, N. - Lippert, C. - Borgwardt, K. - Lawrence, N. D. - Stegle, O.
Journal: Bioinformatics

MOTIVATION: Genomic studies have revealed a substantial heritable component of the transcriptional state of the cell. To fully understand the genetic regulation of gene expression variability, it is important to study the effect of genotype in the context of external factors such as alternative environmental conditions. In model systems, explicit environmental perturbations have been considered for this purpose, allowing to directly test for environment-specific genetic effects. However, such experiments are limited to species that can be profiled in controlled environments, hampering their use in important systems such as human. Moreover, even in seemingly tightly regulated experimental conditions, subtle environmental perturbations cannot be ruled out, and hence unknown environmental influences are frequent. Here, we propose a model-based approach to simultaneously infer unmeasured environmental factors from gene expression profiles and use them in genetic analyses, identifying environment-specific associations between polymorphic loci and individual gene expression traits. RESULTS: In extensive simulation studies, we show that our method is able to accurately reconstruct environmental factors and their interactions with genotype in a variety of settings. We further illustrate the use of our model in a real-world dataset in which one environmental factor has been explicitly experimentally controlled. Our method is able to accurately reconstruct the true underlying environmental factor even if it is not given as an input, allowing to detect genuine genotype-environment interactions. In addition to the known environmental factor, we find unmeasured factors involved in novel genotype-environment interactions. Our results suggest that interactions with both known and unknown environmental factors significantly contribute to gene expression variability. AVAILABILITY: and implementation: Software available at http://pmbio.github.io/envGPLVM/. CONTACT: oliver.stegle@ebi.ac.uk or nicolo.fusi@sheffield.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

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A tool for RNA sequencing sample identity check.

Publication Date: 2013 Jun 1 PMID: 23559639
Authors: Huang, J. - Chen, J. - Lathrop, M. - Liang, L.
Journal: Bioinformatics

SUMMARY: RNA sequencing data are becoming a major method of choice to study transcriptomes, including the mapping of gene expression quantitative trait loci (eQTLs). RNA sample contamination or swapping is a serious problem for downstream analysis and may result in false discovery and lose power to detect the true biological relationships. When genetic data are available, for example, in eQTL studies or samples have been previously genotyped or DNA sequenced, it is possible to combine genetic data and RNA-seq data to detect sample contamination and resolve sample swapping problems. In this article, we introduce a tool (IDCheck) that allows easy assessment of concordance between genotype (from SNP arrays or DNA sequencing) and gene expression (RNA-seq) samples. IDCheck compares the identity of RNA-seq reads and SNP genotypes using a likelihood-based method. Based on maximum likelihood estimates of relevant parameters, we can detect sample contamination and identify correct sample pairs when swapping occurs. Our tool provides an efficient and convenient way to evaluate and resolve these problems. AVAILABILITY: A complete description of the software is included on the application home page. The software is freely available in the public domain at http://eqtl.rc.fas.harvard.edu/idcheck/. CONTACT: lliang@hsph.harvard.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Bayesian hierarchical model of protein-binding microarray k-mer data reduces noise and identifies transcription factor subclasses and preferred k-mers.

Publication Date: 2013 Jun 1 PMID: 23559638
Authors: Jiang, B. - Liu, J. S. - Bulyk, M. L.
Journal: Bioinformatics

MOTIVATION: Sequence-specific transcription factors (TFs) regulate the expression of their target genes through interactions with specific DNA-binding sites in the genome. Data on TF-DNA binding specificities are essential for understanding how regulatory specificity is achieved. RESULTS: Numerous studies have used universal protein-binding microarray (PBM) technology to determine the in vitro binding specificities of hundreds of TFs for all possible 8 bp sequences (8mers). We have developed a Bayesian analysis of variance (ANOVA) model that decomposes these 8mer data into background noise, TF familywise effects and effects due to the particular TF. Adjusting for background noise improves PBM data quality and concordance with in vivo TF binding data. Moreover, our model provides simultaneous identification of TF subclasses and their shared sequence preferences, and also of 8mers bound preferentially by individual members of TF subclasses. Such results may aid in deciphering cis-regulatory codes and determinants of protein-DNA binding specificity. Availability and implementation: Source code, compiled code and R and Python scripts are available from http://thebrain.bwh.harvard.edu/hierarchicalANOVA. CONTACT: bojiang83@gmail.com or mlbulyk@receptor.med.harvard.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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PathVisio-Faceted Search: an exploration tool for multi-dimensional navigation of large pathways.

Publication Date: 2013 Jun 1 PMID: 23547033
Authors: Fried, J. Y. - van Iersel, M. P. - Aladjem, M. I. - Kohn, K. W. - Luna, A.
Journal: Bioinformatics

Purpose: The PathVisio-Faceted Search plugin helps users explore and understand complex pathways by overlaying experimental data and data from webservices, such as Ensembl BioMart, onto diagrams drawn using formalized notations in PathVisio. The plugin then provides a filtering mechanism, known as a faceted search, to find and highlight diagram nodes (e.g. genes and proteins) of interest based on imported data. The tool additionally provides a flexible scripting mechanism to handle complex queries. AVAILABILITY: The PathVisio-Faceted Search plugin is compatible with PathVisio 3.0 and above. PathVisio is compatible with Windows, Mac OS X and Linux. The plugin, documentation, example diagrams and Groovy scripts are available at http://PathVisio.org/wiki/PathVisioFacetedSearchHelp. The plugin is free, open-source and licensed by the Apache 2.0 License. CONTACT: augustin@mail.nih.gov or jakeyfried@gmail.com.

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Fast simulation of reconstructed phylogenies under global time-dependent birth-death processes.

Publication Date: 2013 Jun 1 PMID: 23543414
Authors: Hohna, S.
Journal: Bioinformatics

MOTIVATION: Diversification rates and patterns may be inferred from reconstructed phylogenies. Both the time-dependent and the diversity-dependent birth-death process can produce the same observed patterns of diversity over time. To develop and test new models describing the macro-evolutionary process of diversification, generic and fast algorithms to simulate under these models are necessary. Simulations are not only important for testing and developing models but play an influential role in the assessment of model fit. RESULTS: In the present article, I consider as the model a global time-dependent birth-death process where each species has the same rates but rates may vary over time. For this model, I derive the likelihood of the speciation times from a reconstructed phylogenetic tree and show that each speciation event is independent and identically distributed. This fact can be used to simulate efficiently reconstructed phylogenetic trees when conditioning on the number of species, the time of the process or both. I show the usability of the simulation by approximating the posterior predictive distribution of a birth-death process with decreasing diversification rates applied on a published bird phylogeny (family Cettiidae). AVAILABILITY: The methods described in this manuscript are implemented in the R package TESS, available from the repository CRAN (http://cran.r-project.org/web/packages/TESS/). CONTACT: hoehna@math.su.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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FishingCNV: a graphical software package for detecting rare copy number variations in exome-sequencing data.

Publication Date: 2013 Jun 1 PMID: 23539306
Authors: Shi, Y. - Majewski, J.
Journal: Bioinformatics

SUMMARY: Rare copy number variations (CNVs) are frequent causes of genetic diseases. We developed a graphical software package based on a novel approach that can consistently identify CNVs of all types (homozygous deletions, heterozygous deletions, heterozygous duplications) from exome-sequencing data without the need of a paired control. The algorithm compares coverage depth in a test sample against a background distribution of control samples and uses principal component analysis to remove batch effects. It is user friendly and can be run on a personal computer. Availability and implementation: The main scripts are implemented in R (2.15), and the GUI is created using Java 1.6. It can be run on all major operating systems. A non-GUI version for pipeline implementation is also available. The program is freely available online: https://sourceforge.net/projects/fishingcnv/ CONTACT: yuhao.shi@mail.mcgill.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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MCScanX-transposed: detecting transposed gene duplications based on multiple colinearity scans.

Publication Date: 2013 Jun 1 PMID: 23539305
Authors: Wang, Y. - Li, J. - Paterson, A. H.
Journal: Bioinformatics

SUMMARY: Gene duplication occurs via different modes such as segmental and single-gene duplications. Transposed gene duplication, a specific form of single-gene duplication, 'copies' a gene from an ancestral chromosomal location to a novel location. MCScanX is a toolkit for detection and evolutionary analysis of gene colinearity. We have developed MCScanX-transposed, a software package to detect transposed gene duplications that occurred within different epochs, based on execution of MCScanX within and between related genomes. MCScanX-transposed can be also used for integrative analysis of gene duplication modes for a genome and to annotate a gene family of interest with gene duplication modes. AVAILABILITY: MCScanX-transposed is freely available at http://chibba.pgml.uga.edu/mcscan2/transposed/. CONTACT: wyp1125@gmail.com or paterson@plantbio.uga.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Improved ancestry inference using weights from external reference panels.

Publication Date: 2013 Jun 1 PMID: 23539302
Authors: Chen, C. Y. - Pollack, S. - Hunter, D. J. - Hirschhorn, J. N. - Kraft, P. - Price, A. L.
Journal: Bioinformatics

MOTIVATION: Inference of ancestry using genetic data is motivated by applications in genetic association studies, population genetics and personal genomics. Here, we provide methods and software for improved ancestry inference using genome-wide single nucleotide polymorphism (SNP) weights from external reference panels. This approach makes it possible to leverage the rich ancestry information that is available from large external reference panels, without the administrative and computational complexities of re-analyzing the raw genotype data from the reference panel in subsequent studies. RESULTS: We extensively validate our approach in multiple African American, Latino American and European American datasets, making use of genome-wide SNP weights derived from large reference panels, including HapMap 3 populations and 6546 European Americans from the Framingham Heart Study. We show empirically that our approach provides much greater accuracy than either the prevailing ancestry-informative marker (AIM) approach or the analysis of genome-wide target genotypes without a reference panel. For example, in an independent set of 1636 European American genome-wide association study samples, we attained prediction accuracy (R(2)) of 1.000 and 0.994 for the first two principal components using our method, compared with 0.418 and 0.407 using 150 published AIMs or 0.955 and 0.003 by applying principal component analysis directly to the target samples. We finally show that the higher accuracy in inferring ancestry using our method leads to more effective correction for population stratification in association studies. AVAILABILITY: The SNPweights software is available online at http://www.hsph.harvard.edu/faculty/alkes-price/software/. CONTACT: aprice@hsph.harvard.edu or cychen@mail.harvard.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Promoter proximal CTCF binding is associated with an increase in the transcriptional pausing index.

Publication Date: 2012 Oct 9 PMID: 23047559
Authors: Paredes, S. H. - Melgar, M. F. - Sethupathy, P.
Journal: Bioinformatics

MOTIVATION: It has been known for over two decades that after RNA polymerase II (RNAPII) initiates transcription, it can enter in to a paused or stalled state immediately downstream of the transcription start site prior to productive elongation. Recent advances in high-throughput genomic technologies facilitated the discovery that RNAPII pausing at promoters is a widespread, physiologically regulated phenomenon. The molecular underpinnings of pausing are incompletely understood. The CCCTC-factor (CTCF) is a ubiquitous nuclear factor that has diverse regulatory functions, including a recently discovered role in promoting RNAPII pausing at splice sites. RESULTS: In this study, we analyzed CTCF ChIP-seq/ChIP-chip and GRO-seq data from three different cell types, and found that promoter-proximal CTCF binding is significantly associated with RNAPII pausing. CONTACT: praveen_sethupathy@med.unc.edu SUPPLEMENTARY INFORMATION: Supplementary_Material_1.xls.

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