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List of RNA-Seq bioinformatics tools (II)  

2014-02-25 21:11:38|  分类: 生物信息分析 |  标签: |举报 |字号 订阅

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De novo Splice Aligners[edit]

De novo Splice aligners allow the detection of new Splice junctions without need to previous annotated information (some of these tools present annotation as a suplementar option). See also De novo Splice Aligners.

  • ABMapper ABMapper. See also seqanswers/ABMapper.
  • ContextMap ContextMap was developed to overcome some limitations of other mapping approaches, such as resolution of ambiguities. The central idea of this tool is to consider reads in gene expression context, improving this way alignment accuracy. ContextMap can be used as a stand-alone program and supported by mappers producing a SAM file in the output (e.g.: TopHat or MapSplice). In stand-alone mode aligns reads to a genome, to a transcriptome database or both.
  • CRAC CRAC propose a novel way of analyzing reads that integrates genomic locations and local coverage, and detect candidate mutations, indels, splice or fusion junctions in each single read. Importantly, CRAC improves its predictive performance when supplied with e.g. 200 nt reads and should fit future needs of read analyses.
  • GSNAP GSNAP. See also seqanswers/GSNAP.
  • HMMSplicer HMMSplicer can identify canonical and non-canonical splice junctions in short-reads. Firstly, unspliced reads are removed with Bowtie. After that, the remaining reads are one at a time divided in half, then each part is seeded against a genome and the exon borders are determined based on the Hidden Markov Model . A quality score is assigned to each junction, useful to detect false positive rates. See also seqanswers/HMMSplicer.
  • Subread Subread[2] is a superfast, accurate and scalable read aligner. It uses the seed-and-vote mapping paradigm to determine the mapping location of the read by using its largest mappable region. It automatically decides whether the read should be globally mapped or locally mapped. For RNA-seq data, Subread should be used for the purpose of expression analysis. Subread is very powerful in mapping gDNA-seq reads as well. See also seqanswers/Subread.
  • Subjunc Subjunc[2] is a specialized version of Subread. It uses all mappable regions in an RNA-seq read to discover exons and exon-exon junctions. It uses the donor/receptor signals to find the exact splicing locations. Subjunc yields full alignments for every RNA-seq read including exon-spanning reads, in addition to the discovered exon-exon junctions. Subjunc should be used for the purpose of junction detection and genomic variation detection in RNA-seq data. See also seqanswers/Subjunc.
De novo Splice Aligners that also use annotation optionally[edit]
  • GEM.
  • MapNext MapNext. See also seqanswers/MapNext.
  • STAR STAR is an ultrafast tool that employs “sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure”, detects canonical, non-canonical splices junctions and chimeric-fusion sequences. It is already adapted to align long reads (third-generation sequencing technologies) and can reach speeds of 45 million paired reads per hour per processor.[3] See also seqanswers/STAR.
  • TopHat TopHat[4] is prepared to find de novo junctions. TopHat aligns reads in two steps. Firstly, unspliced reads are aligned with Bowtie. After, the aligned reads are assembled with Maq resulting islands of sequences. Secondly, the splice junctions are determined based on the initially unmapped reads and the possible canonical donor and acceptor sites within the island sequences. See also seqanswers/TopHat.
Other Spliced Aligners[edit]
  • G.Mo.R-Se G.Mo.R-Se is a method that uses RNA-Seq reads to build de novo gene models.

Quantitative analysis and Differential Expression[edit]

These tools calculate the abundance of each gene expressed in a RNA-Seq sample (see also Quantification models). Some software are also designed to study the variability of genetic expression between samples (differential expression). Quantitative and differential studies are largely determined by the quality of reads alignment and accuracy of isoforms reconstruction. See a comparative study of differential expression methods and Which method should you use for normalization of rna-seq data?.

  • ALDex ALDex.
  • Alexa-Seq Alexa-Seq is a pipeline that makes possible to perform gene expression analysis, transcript specific expression analysis, exon junction expression and quantitative alternative analysis. Allows wide alternative expression visualization, statistics and graphs. See also seqanswers/Alexa-Seq.
  • ASC ASC. See also seqanswers/ASC.
  • BaySeq BaySeq is a Bioconductor package to identify differential expression using next-generation sequencing data, via empiricalBayesian methods. There is an option of using the “snow” package for parallelisation of computer data processing, recommended when dealing with large data sets. See also seqanswers/BaySeq.
  • BBSeq BBSeq. See also seqanswers/BBSeq.
  • BitSeq BitSeq.
  • CEDER CEDER.
  • CPTRA CPTRA.
  • casper casper is a Bioconductor package to quantify expression at the isoform level. It combines using informative data summaries, flexible estimation of experimental biases and statistical precision considerations which (reportedly) provide substantial reductions in estimation error.
  • Cufflinks Cufflinks is appropriate to measure global de novo transcript isoform expression. It performs assembly of transcripts, estimation of abundances and determines differential expression (Cuffdiff) and regulation in RNA-Seq samples. See alsoseqanswers/Cufflinks .[5]
  • DESeq DESeq is a Bioconductor package to perform differential gene expression analysis based on negative binomial distribution. See also seqanswers/DESeq.
  • DEGSeq DEGSeq. See also seqanswers/DEGSeq.
  • DEXSeq DEXSeq is Bioconductor package that finds differential differential exon usage based on RNA-Seq exon counts between samples. DEXSeq employs negative binomial distribuition, provides options to visualization and exploration of the results.
  • DEXUS dexus is a Bioconductor package that identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions.[6] In contrast to other methods, DEXUS does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript.
  • DiffSplice DiffSplice is a method for differential expression detection and visualization, not dependent on gene annotations. This method is supported on identification of alternative splicing modules (ASMs) that diverge in the different isoforms. A non-parametric test is applied to each ASM to identify significant differential transcription with a measured false discovery rate.
  • EBSeq EBSeq.
  • EdgeR EdgeR is a R package for analysis of differential expression of data from DNA sequencing methods, like RNA-Seq, SAGE or ChIP-Seq data. edgeR employs statistical methods supported on negative binomial distribution as a model for count variability. See also seqanswers/EdgeR.
  • ESAT ESAT The End Sequence Analysis Toolkit (ESAT) is specially designing to be applied for quantification of annotation of specialized RNA-Seq gene libraries that target the 5' or 3' ends of transcripts.
  • eXpress eXpress performance includes transcript-level RNA-Seq quantification, allele-specific and haplotype analysis and can estimate transcript abundances of the multiple isoforms present in a gene. Although could be coupled directly with aligners (like Bowtie), eXpress can also be used with de novo assemblers and thus is not needed a reference genome to perform alignment. It runs on Linux, Mac and Windows.
  • ERANGE ERANGE performs alignment, normalization and quantification of expressed genes. See also seqanswers/ERANGE.
  • featureCounts featureCounts an efficient general-purpose read quantifier. It is part of the SourceForge Subread package andBioconductor Rsubread package.
  • FDM FDM
  • GPSeq GPSeq
  • MATS MATS.
  • MMSEQ MMSEQ is a pipeline for estimating isoform expression and allelic imbalance in diploid organisms based on RNA-Seq. The pipeline employs tools like Bowtie, TopHat, ArrayExpressHTS and SAMtools. Also, edgeR or DESeq to perform differential expression. See also seqanswers/MMSEQ.
  • Myrna Myrna is a pipeline tool that runs in a cloud environment (Elastic MapReduce) or in a unique computer for estimating differential gene expression in RNA-Seq datasets. Bowtie is employed for short read alignment and R algorithms for interval calculations, normalization, and statistical processing. See also seqanswers/Myrna.
  • NEUMA NEUMA is a tool to estimate RNA abundances using length normalization, based on uniquely aligned reads and mRNA isoform models. NEUMA uses known transcriptome data available in databases like RefSeq.
  • NOISeq NOISeq. See also seqanswers/NOISeq.
  • NPEBseq NPEBseq is a nonparametric empirical bayesian- based method for differential expression analysis.
  • NSMAP NSMAP allows inference of isoforms as well estimation of expression levels, without annotated information. The exons are aligned and splice junctions are identified using TopHat. All the possible isoforms are computed by combination of the detected exons.
  • RNAeXpress RNAeXpress Can be run with Java GUI or command line on Mac, Windows and Linux. Can be configured to perform read counting, feature detection or GTF comparison on mapped rnaseq data.
  • rSeq rSeq
  • RSEM RSEM. See also seqanswers/RSEM.
  • rQuant rQuant is a web service (Galaxy (computational biology) installation) that determines abundances of transcripts per gene locus, based on quadratic programming. rQuant is able to evaluate biases introduced by experimental conditions. A combination of tools is employed: PALMapper (reads alignment), mTiM and mGene (inference of new transcripts).
  • Scotty Scotty Performs power analysis to estimate the number of replicates and depth of sequencing required to call differential expression.
  • SpliceTrap SpliceTrap.
  • SplicingCompass SplicingCompass.
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