Showing papers in "Bioinformatics in 2014"
TL;DR: Timmomatic is developed as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data and is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.
Abstract: Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.
Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.
Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic
Contact: ed.nehcaa-htwr.1oib@ledasu
Supplementary information: Supplementary data are available at Bioinformatics online.
39,291 citations
TL;DR: This work presents some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees.
Abstract: Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting postanalyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU
23,838 citations
TL;DR: FeatureCounts as discussed by the authors is a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments, which implements highly efficient chromosome hashing and feature blocking techniques.
Abstract: MOTIVATION: Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. RESULTS: We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. AVAILABILITY AND IMPLEMENTATION: featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
14,103 citations
TL;DR: Prokka is introduced, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer, and produces standards-compliant output files for further analysis or viewing in genome browsers.
Abstract: UNLABELLED: The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. AVAILABILITY AND IMPLEMENTATION: Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/.
10,432 citations
TL;DR: A new Java-based architecture for the widely used protein function prediction software package InterProScan is described, resulting in a flexible and stable system that is able to use both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis.
Abstract: Motivation: Robust, large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterise many millions of sequences. Here we describe a new Java-based architecture for the widely-used protein function prediction software package InterProScan. Developments include improvements and additions to the outputs of the software and the complete re-implementation of the software framework, resulting in a flexible and stable system that is able to utilise both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis. InterProScan is freely available for download from the EMBl-EBI FTP site and the (open) source code is hosted at Google Code. Availability: InterProScan is distributed via FTP at ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/5/ and the source code is available from http://code.google.com/p/interproscan/. Contact: http://www.ebi.ac.uk/support or interhelp@ebi.ac.uk
5,434 citations
TL;DR: This work presents a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base and extends the method to predict downstream effects on biological functions and diseases.
Abstract: Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets. Results: We present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets. Availability: The causal analytics tools ‘Upstream Regulator Analysis’, ‘Mechanistic Networks’, ‘Causal Network Analysis’ and ‘Downstream Effects Analysis’ are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com). Supplementary information: Supplementary material is available at Bioinformatics online.
3,828 citations
TL;DR: The PEAR software for merging raw Illumina paired-end reads from target fragments of varying length evaluates all possible paired- end read overlaps and does not require the target fragment size as input, and implements a statistical test for minimizing false-positive results.
Abstract: Motivation The Illumina paired-end sequencing technology can generate reads from both ends of target DNA fragments, which can subsequently be merged to increase the overall read length. There already exist tools for merging these paired-end reads when the target fragments are equally long. However, when fragment lengths vary and, in particular, when either the fragment size is shorter than a single-end read, or longer than twice the size of a single-end read, most state-of-the-art mergers fail to generate reliable results. Therefore, a robust tool is needed to merge paired-end reads that exhibit varying overlap lengths because of varying target fragment lengths. Results We present the PEAR software for merging raw Illumina paired-end reads from target fragments of varying length. The program evaluates all possible paired-end read overlaps and does not require the target fragment size as input. It also implements a statistical test for minimizing false-positive results. Tests on simulated and empirical data show that PEAR consistently generates highly accurate merged paired-end reads. A highly optimized implementation allows for merging millions of paired-end reads within a few minutes on a standard desktop computer. On multi-core architectures, the parallel version of PEAR shows linear speedups compared with the sequential version of PEAR. Availability and implementation PEAR is implemented in C and uses POSIX threads. It is freely available at http://www.exelixis-lab.org/web/software/pear.
3,270 citations
TL;DR: A suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data are described that include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale.
Abstract: Motivation The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Results Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. Availability and implementation http://bioconductor.org/packages/release/bioc/html/minfi.html. Contact khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary information Supplementary data are available at Bioinformatics online.
2,961 citations
TL;DR: UNLABELLED STAMP is a graphical software package that provides statistical hypothesis tests and exploratory plots for analysing taxonomic and functional profiles and a user-friendly graphical interface permits easy exploration of statistical results and generation of publication-quality plots.
Abstract: Summary: STAMP is a graphical software package that provides statistical hypothesis tests and exploratory plots for analysing taxonomic and functional profiles. It supports tests for comparing pairs of samples or samples organized into two or more treatment groups. Effect sizes and confidence intervals are provided to allow critical assessment of the biological relevancy of test results. A user-friendly graphical interface permits easy exploration of statistical results and generation of publication-quality plots.
Availability and implementation: STAMP is licensed under the GNU GPL. Python source code and binaries are available from our website at: http://kiwi.cs.dal.ca/Software/STAMP
Contact: moc.liamg@skrap.navonod
Supplementary information: Supplementary data are available at Bioinformatics online.
2,739 citations
TL;DR: The circlize package is presented, which provides an implementation of circular layout generation in R as well as an enhancement of available software and the flexibility of this package is based on the usage of low-level graphics functions such that self-defined high- level graphics can be easily implemented by users for specific purposes.
Abstract: Summary Circular layout is an efficient way for the visualization of huge amounts of genomic information. Here we present the circlize package, which provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of this package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, circlize gives users more convenience and freedom to design figures for better understanding genomic patterns behind multi-dimensional data. Availability and implementation circlize is available at the Comprehensive R Archive Network (CRAN): http://cran.r-project.org/web/packages/circlize/
2,276 citations
TL;DR: AliView is an alignment viewer and editor designed to meet the requirements of next-generation sequencing era phylogenetic datasets and works as an easy-to-use alignment editor for small as well as large datasets.
Abstract: Summary: AliView is an alignment viewer and editor designed to meet the requirements of next-generation sequencing era phylogenetic datasets. AliView handles alignments of unlimited size in the formats most commonly used, i.e. FASTA, Phylip, Nexus, Clustal and MSF. The intuitive graphical interface makes it easy to inspect, sort, delete, merge and realign sequences as part of the manual filtering process of large datasets. AliView also works as an easy-to-use alignment editor for small as well as large datasets.
Availability and implementation: AliView is released as open-source software under the GNU General Public License, version 3.0 (GPLv3), and is available at GitHub (www.github.com/AliView). The program is cross-platform and extensively tested on Linux, Mac OS X and Windows systems. Downloads and help are available at http://ormbunkar.se/aliview
Contact: es.uu.cbe@nossral.sredna
Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: A novel algorithm termed Cas-OFFinder that searches for potential off-target sites in a given genome or user-defined sequences and allows variations in protospacer-adjacent motif sequences recognized by Cas9, the essential protein component in RGENs.
Abstract: Summary: The Type II clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system is an adaptive immune response in prokaryotes, protecting host cells against invading phages or plasmids by cleaving these foreign DNA species in a targeted manner. CRISPR/Cas-derived RNA-guided engineered nucleases (RGENs) enable genome editing in cultured cells, animals and plants, but are limited by off-target mutations. Here, we present a novel algorithm termed Cas-OFFinder that searches for potential off-target sites in a given genome or user-defined sequences. Unlike other algorithms currently available for identification of RGEN off-target sites, Cas-OFFinder is not limited by the number of mismatches and allows variations in protospacer-adjacent motif sequences recognized by Cas9, the essential protein component in RGENs. Cas-OFFinder is available as a command-line program or accessible via our website.
Availability and implementation: Cas-OFFinder free access at http://www.rgenome.net/cas-offinder.
Contact: rk.ca.uns@uaseab or rk.ca.uns@10miksj
TL;DR: This paper presents a user-friendly protein docking server, based on the rigid-body docking programs ZDOCK and M-ZDOCK, to predict structures of protein-protein complexes and symmetric multimers, and provides options for users to guide the scoring and the selection of output models.
Abstract: Summary: Protein–protein interactions are essential to cellular and immune function, and in many cases, because of the absence of an experimentally determined structure of the complex, these interactions must be modeled to obtain an understanding of their molecular basis. We present a user-friendly protein docking server, based on the rigid-body docking programs ZDOCK and M-ZDOCK, to predict structures of protein–protein complexes and symmetric multimers. With a goal of providing an accessible and intuitive interface, we provide options for users to guide the scoring and the selection of output models, in addition to dynamic visualization of input structures and output docking models. This server enables the research community to easily and quickly produce structural models of protein–protein complexes and symmetric multimers for their own analysis.
Availability: The ZDOCK server is freely available to all academic and non-profit users at: http://zdock.umassmed.edu. No registration is required.
Contact: ude.demssamu@ecreip.nairb or ude.demssamu@gnew.gnipihz
TL;DR: ThunderSTORM is an open-source, interactive and modular plug-in for ImageJ designed for automated processing, analysis and visualization of data acquired by single-molecule localization microscope methods such as photo-activated localization microscopy and stochastic optical reconstruction microscopy.
Abstract: Summary: ThunderSTORM is an open-source, interactive and modular plug-in for ImageJ designed for automated processing, analysis and visualization of data acquired by single-molecule localization microscopy methods such as photo-activated localization microscopy and stochastic optical reconstruction microscopy. ThunderSTORM offers an extensive collection of processing and post-processing methods so that users can easily adapt the process of analysis to their data. ThunderSTORM also offers a set of tools for creation of simulated data and quantitative performance evaluation of localization algorithms using Monte Carlo simulations.
Availability and implementation: ThunderSTORM and the online documentation are both freely accessible at https://code.google.com/p/thunder-storm/
Contact: zc.inuc.1fl@negah.yug
Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: A new approach to solve the ‘molecular graphics problem’ is described, which shares the work between GPU and multiple CPU cores, generates high-quality results with perfectly round spheres, shadows and ambient lighting and requires only OpenGL 1.0 functionality.
Abstract: SUMMARY: Today's graphics processing units (GPUs) compose the scene from individual triangles. As about 320 triangles are needed to approximate a single sphere-an atom-in a convincing way, visualizing larger proteins with atomic details requires tens of millions of triangles, far too many for smooth interactive frame rates. We describe a new approach to solve this 'molecular graphics problem', which shares the work between GPU and multiple CPU cores, generates high-quality results with perfectly round spheres, shadows and ambient lighting and requires only OpenGL 1.0 functionality, without any pixel shader Z-buffer access (a feature which is missing in most mobile devices). AVAILABILITY AND IMPLEMENTATION: YASARA View, a molecular modeling program built around the visualization algorithm described here, is freely available (including commercial use) for Linux, MacOS, Windows and Android (Intel) from www.YASARA.org. CONTACT: elmar@yasara.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
TL;DR: ASTRAL is a fast method for estimating species trees from multiple genes that is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods.
Abstract: Motivation: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions.
Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees.
Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral.
Contact: ude.sionilli@wonraw
Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: Protter, a web-based tool that supports interactive protein data analysis and hypothesis generation by visualizing both annotated sequence features and experimental proteomic data in the context of protein topology, is presented.
Abstract: Summary: The ability to integrate and visualize experimental proteomic evidence in the context of rich protein feature annotations represents an unmet need of the proteomics community. Here we present Protter, a web-based tool that supports interactive protein data analysis and hypothesis generation by visualizing both annotated sequence features and experimental proteomic data in the context of protein topology. Protter supports numerous proteomic file formats and automatically integrates a variety of reference protein annotation sources, which can be readily extended via modular plugins. A built-in export function produces publication-quality customized protein illustrations, also for large datasets. Visualizations of surfaceome datasets show the specific utility of Protter for the integrated visual analysis of membrane proteins and peptide selection for targeted proteomics. Availability and implementation: The Protter web application is available at http://wlab.ethz.ch/protter. Source code and installation instructions are available at http://ulo.github.io/Protter/.
TL;DR: A method to infer relationships among quartets of taxa under the coalescent model using techniques from algebraic statistics is developed, and uncertainty in the estimated relationships is quantified using the nonparametric bootstrap.
Abstract: Motivation: Increasing attention has been devoted to estimation of species-level phylogenetic relationships under the coalescent model. However, existing methods either use summary statistics (gene trees) to carry out estimation, ignoring an important source of variability in the estimates, or involve computationally intensive Bayesian Markov chain Monte Carlo algorithms that do not scale well to whole-genome datasets.
Results: We develop a method to infer relationships among quartets of taxa under the coalescent model using techniques from algebraic statistics. Uncertainty in the estimated relationships is quantified using the nonparametric bootstrap. The performance of our method is assessed with simulated data. We then describe how our method could be used for species tree inference in larger taxon samples, and demonstrate its utility using datasets for Sistrurus rattlesnakes and for soybeans.
Availability and implementation: The method to infer the phylogenetic relationship among quartets is implemented in the software SVDquartets, available at www.stat.osu.edu/∼lkubatko/software/SVDquartets.
Contact: ude.uso.tats@oktabukl
Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: DIYABC v2.0 implements a number of new features and analytical methods, including efficient Bayesian model choice using linear discriminant analysis on summary statistics and the serial launching of multiple post-processing analyses.
Abstract: DIYABC is a software package for a comprehensive analysis of population history using approximate Bayesian computation on DNA polymorphism data. Version 2.0 implements a number of new features and analytical methods. It allows (i) the analysis of single nucleotide polymorphism data at large number of loci, apart from microsatellite and DNA sequence data, (ii) efficient Bayesian model choice using linear discriminant analysis on summary statistics and (iii) the serial launching of multiple post-processing analyses. DIYABC v2.0 also includes a user-friendly graphical interface with various new options. It can be run on three operating systems: GNU/Linux, Microsoft Windows and Apple Os X. Freely available with a detailed notice document and example projects to academic users at http://www1.montpellier.inra.fr/CBGP/diyabc CONTACT: estoup@supagro.inra.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
TL;DR: By investigating false heterozygous calls in the haploid genome, the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample are identified as the two major sources of errors, which press for continued improvements in these two areas.
Abstract: Motivation: Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods.
Results: We made 10 single nucleotide polymorphism and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10–15 kb, but the error rate of post-filtered calls is reduced to 1 in 100–200 kb without significant compromise on the sensitivity.
Availability and implementation: BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp.
Contact: gro.etutitsnidaorb@ilgneh
Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: This work presents UNLABELLED MSstats, an R package for statistical relative quantification of proteins and peptides in mass spectrometry-based proteomics, which supports label-free and label-based experimental workflows and data-dependent, targeted andData-independent spectral acquisition.
Abstract: UNLABELLED MSstats is an R package for statistical relative quantification of proteins and peptides in mass spectrometry-based proteomics. Version 2.0 of MSstats supports label-free and label-based experimental workflows and data-dependent, targeted and data-independent spectral acquisition. It takes as input identified and quantified spectral peaks, and outputs a list of differentially abundant peptides or proteins, or summaries of peptide or protein relative abundance. MSstats relies on a flexible family of linear mixed models. AVAILABILITY AND IMPLEMENTATION The code, the documentation and example datasets are available open-source at www.msstats.org under the Artistic-2.0 license. The package can be downloaded from www.msstats.org or from Bioconductor www.bioconductor.org and used in an R command line workflow. The package can also be accessed as an external tool in Skyline (Broudy et al., 2014) and used via graphical user interface.
TL;DR: It is shown that mCSM can predict stability changes of a wide range of mutations occurring in the tumour suppressor protein p53, demonstrating the applicability of the proposed method in a challenging disease scenario.
Abstract: Motivation: Mutations play fundamental roles in evolution by introducing diversity into genomes. Missense mutations in structural genes may become either selectively advantageous or disadvantageous to the organism by affecting protein stability and/or interfering with interactions between partners. Thus, the ability to predict the impact of mutations on protein stability and interactions is of significant value, particularly in understanding the effects of Mendelian and somatic mutations on the progression of disease. Here, we propose a novel approach to the study of missense mutations, called mCSM, which relies on graph-based signatures. These encode distance patterns between atoms and are used to represent the protein residue environment and to train predictive models. To understand the roles of mutations in disease, we have evaluated their impacts not only on protein stability but also on protein–protein and protein–nucleic acid interactions. Results: We show that mCSM performs as well as or better than other methods that are used widely. The mCSM signatures were successfully used in different tasks demonstrating that the impact of a mutation can be correlated with the atomic-distance patterns surrounding an amino acid residue. We showed that mCSM can predict stability changes of a wide range of mutations occurring in the tumour suppressor protein p53, demonstrating the applicability of the proposed method in a challenging disease scenario. Availability and implementation: A web server is available at http:// structure.bioc.cam.ac.uk/mcsm.
TL;DR: The conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution, compared with two other popular transcriptome assemblers.
Abstract: Motivation: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 � 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge. Results: Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these wellannotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution. Availability and implementation: Source code and user manual are available at http://sourceforge.net/projects/soapdenovotrans/. Contact: xieyl@genomics.cn or bgi-soap@googlegroups.com Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: It is shown through reanalysis of an empirical RADseq dataset that indels are a common feature of such data, even at shallow phylogenetic scales, and PyRAD uses parallel processing as well as an optional hierarchical clustering method, which allows it to rapidly assemble phylogenetic datasets with hundreds of sampled individuals.
Abstract: Motivation: Restriction-site associated genomic markers are a powerful tool for investigating evolutionary questions at the population level, but are limited in their utility at deeper phylogenetic scales where fewer orthologous loci are typically recovered across disparate taxa. While this limitation stems in part from mutations to restriction recognition sites that disrupt data generation, an additional source of data loss comes from the failure to identify homology during bioinformatic analyses. Clustering methods that allow for lower similarity thresholds and the inclusion of indel variation will perform better at assembling RADseq loci at the phylogenetic scale. Results: PyRAD is a pipeline to assemble de novo RADseq loci with the aim of optimizing coverage across phylogenetic data sets. It utilizes a wrapper around an alignment-clustering algorithm which allows for indel variation within and between samples, as well as for incomplete overlap among reads (e.g., paired-end). Here I compare PyRAD with the program Stacks in their performance analyzing a simulated RADseq data set that includes indel variation. Indels disrupt clustering of homologous loci in Stacks but not in PyRAD, such that the latter recovers more shared loci across disparate taxa. I show through re-analysis of an empirical RADseq data set that indels are a common feature of such data, even at shallow phylogenetic scales. PyRAD utilizes parallel processing as well as an optional hierarchical clustering method which allow it to rapidly assemble phylogenetic data sets with hundreds of sampled individuals. Availability: Software is written in Python and freely available at http://www.dereneaton.com/software/ Supplement: Scripts to completely reproduce all simulated and empirical analyses are available in the Supplementary Materials.
TL;DR: An integrated analysis pipeline offering a choice of the most popular normalization methods while also introducing new methods for calling differentially methylated regions and detecting copy number aberrations is presented.
Abstract: The Illumina Infinium HumanMethylation450 BeadChip is a new platform for high-throughput DNA methylation analysis. Several methods for normalization and processing of these data have been published recently. Here we present an integrated analysis pipeline offering a choice of the most popular normalization methods while also introducing new methods for calling differentially methylated regions and detecting copy number aberrations. Availability and implementation: ChAMP is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at bioconductor.org
TL;DR: SAMBLASTER as mentioned in this paper is a post-passing tool that can reduce the number of read, write, sort and compress large BAM files multiple times by marking duplicates in read-sorted SAM files.
Abstract: Motivation: Illumina DNA sequencing is now the predominant source of raw genomic data, and data volumes are growing rapidly. Bioinformatic analysis pipelines are having trouble keeping pace. A common bottleneck in such pipelines is the requirement to read, write, sort and compress large BAM files multiple times.
Results: We present SAMBLASTER, a tool that reduces the number of times such costly operations are performed. SAMBLASTER is designed to mark duplicates in read-sorted SAM files as a piped post-pass on DNA aligner output before it is compressed to BAM. In addition, it can simultaneously output into separate files the discordant read-pairs and/or split-read mappings used for structural variant calling. As an alignment post-pass, its own runtime overhead is negligible, while dramatically reducing overall pipeline complexity and runtime. As a stand-alone duplicate marking tool, it performs significantly better than PICARD or SAMBAMBA in terms of both speed and memory usage, while achieving nearly identical results.
Availability and implementation: SAMBLASTER is open-source C++ code and freely available for download from https://github.com/GregoryFaust/samblaster.
Contact: ude.ainigriv@y4hmi
TL;DR: LoRDEC, a hybrid error correction method that builds a succinct de Bruijn graph representing the short reads, and seeks a corrective sequence for each erroneous region in the long reads by traversing chosen paths in the graph is presented.
Abstract: Motivation: PacBio single molecule real-time sequencing is a third-generation sequencing technique producing long reads, with com-paratively lower throughput and higher error rate. Errors include numerous indels and complicate downstream analysis like mapping or de novo assembly. A hybrid strategy that takes advantage of the high accuracy of second-generation short reads has been proposed for correcting long reads. Mapping of short reads on long reads pro-vides sufficient coverage to eliminate up to 99% of errors, however, at the expense of prohibitive running times and considerable amounts of disk and memory space. Results: We present LoRDEC, a hybrid error correction method that builds a succinct de Bruijn graph representing the short reads, and seeks a corrective sequence for each erroneous region in the long reads by traversing chosen paths in the graph. In comparison, LoRDEC is at least six times faster and requires at least 93% less memory or disk space than available tools, while achieving comparable accuracy.
TL;DR: This work presents geiger v2.0, a complete overhaul of the popular R package geiger, which reimplemented existing methods with more efficient algorithms and developed several new approaches for accomodating heterogeneous models and data types.
Abstract: Summary: Phylogenetic comparative methods are essential for addressing evolutionary hypotheses with interspecific data. The scale and scope of such data have increased dramatically in the past few years. Many existing approaches are either computationally infeasible or inappropriate for data of this size. To address both of these problems, we present geiger v2.0, a complete overhaul of the popular R package geiger. We have reimplemented existing methods with more efficient algorithms and have developed several new approaches for accomodating heterogeneous models and data types. Availability and implementation: This R package is available on the CRAN repository http://cran.r-project.org/web/packages/geiger/. All source code is also available on github http://github.com/mwpennell/geiger-v2. geiger v2.0 depends on the ape package. Contact: mwpennell@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online
TL;DR: Kmergenie as discussed by the authors constructs approximate abundance histograms with several orders of magnitude performance improvement over traditional methods and then presents a fast heuristic that uses the generated abundance histogram for putative k values to estimate the best possible value of k.
Abstract: 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 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.
TL;DR: Comprehensive testing indicates MSIsensor, a C++ program for automatically detecting somatic microsatellite changes, is an efficient and effective tool for deriving MSI status from standard tumor-normal paired sequence data.
Abstract: Motivation: Microsatellite instability (MSI) is an important indicator of larger genome instability and has been linked to many genetic diseases, including Lynch syndrome. MSI status is also an independent prognostic factor for favorable survival in multiple cancer types, such as colorectal and endometrial. It also informs the choice of chemotherapeutic agents. However, the current PCR–electrophoresis-based detection procedure is laborious and time-consuming, often requiring visual inspection to categorize samples. We developed MSIsensor, a Cþþ program for automatically detecting somatic microsatellite changes. It computes length distributions of microsatellites per site in paired tumor and normal sequence data, subsequently using these to statistically compare observed distributions in both samples. Comprehensive testing indicates MSIsensor is an efficient and effective tool for deriving MSI status from standard tumor-normal paired sequence data. Availability and implementation: https://github.com/ding-lab/ msisensor