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List of RNA-Seq bioinformatics tools (III)  

2014-02-25 21:13:31|  分类: 生物信息分析 |  标签: |举报 |字号 订阅

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Multi-tool solutions[edit]

  • DEB DEB is a web-interface/pipeline that permits to compare results of significantly expressed genes from different tools. Currently are available three algorithms: edgeR, DESeq and bayseq.

Workbench (analysis pipeline / integrated solutions)[edit]

See also an interesting blog 16 rna-seq tools you have to consider for your analysis pipeline.

Commercial Solutions[edit]

Open Source Solutions[edit]

  • ArrayExpressHTS ArrayExpressHTS (and ebi_ArrayExpressHTS) is a BioConductor package that allows preprocessing, quality assessment and estimation of expression of RNA-Seq datasets. It can be run remotely at the European Bioinformatics Institute cloud or locally. The package makes use of several tools: ShortRead (quality control), Bowtie, TopHat or BWA (alignment to a reference genome), SAMtools format, Cufflinks or MMSEQ (expression estimation). See also seqanswers/ArrayExpressHTS.
  • Chipster Chipster.
  • easyRNASeq easyRNASeq.
  • ExpressionPlot ExpressionPlot.
  • FX FX.
  • Galaxy: Galaxy is a general purpose workbench platform for computational biology. There are several publicly accessible Galaxy servers that support RNA-Seq tools and workflows, including NBIC's Andromeda, the CBIIT-Giga server, the Galaxy Project'spublic server, the GeneNetwork Galaxy server, the University of Oslo's Genomic Hyperbrowser, URGI's server (which supports S-MART), and many others.
  • GENE-Counter GENE-Counter is a Perl pipeline for RNA-Seq differential gene expression analyses. Gene-counter performs alignments with CASHX, Bowtie, BWA or other SAM output aligner. Differential gene expression is run with three optional packages (NBPSeq, edgeR and DESeq) using negative binomial distribution methods. Results are stored in a MySQL database to make possible additional analyses.
  • GenePattern GenePattern offers integrated solutions to RNA-Seq analysis (Broad Institute).
  • GeneProf GeneProf: Freely accessible, easy to use analysis pipelines for RNA-seq and ChIP-seq experiments.
  • MultiExperiment Viewer (MeV) MeV is suitable to perform analysis, data mining and visualization of large-scale genomic data. The MeV modules include a variety of algorithms to execute tasks like Clustering and Classification, Student's t-test, Gene Set Enrichment Analysis or Significance Analysis. MeV runs on Java. See also seqanswers/MeV.
  • NGS-Trex NGS-Trex.
  • NGSUtils NGSUtils.
  • RobiNA RobiNA provides a user graphical interface to deal with R/BioConductor packages. RobiNA provides a package that automatically installs all required external tools (R/Bioconductor frameworks and Bowtie). This tool offers a diversity of quality control methods and the possibility to produce many tables and plots supplying detailed results for differential expression. Furthermore, the results can be visualized and manipulated with MapMan and PageMan. RobiNA runs on Java version 6.
  • S-MART S-MART handles mapped RNA-Seq data, and performs essentially data manipulation (selection/exclusion of reads, clustering and differential expression analysis) and visualization (read information, distribution, comparison with epigenomic ChIP-Seq data). It can be run on any laptop by a person without computer background. A friendly graphical user interface makes easy the operation of the tools. See also seqanswers/S-MART.
  • Taverna Taverna.
  • TCW TCW. TCW is a Transcriptome Computational Workbench.
  • wapRNA wapRNA.

Alternative Splicing Analysis[edit]

  • MISO MISO quantifies the expression level of splice variants from RNA-Seq data and is able to recognize differentially regulated exons/isoforms across different samples. MISO uses a probabilistic method (Bayesian inference) to calculate the probability of the reads origin. See also seqanswers/MISO.
  • rDiff rDiff Can detect differential RNA processing with or without gene annotation.
  • SAJR SAJR calculates the number of the reads that confirms segment (part of gene between two nearest splice sites) inclusion or explusion and then model these counts by GLM with quasibinomial distribution to account for biological variability.

Bias Correction[edit]

  • EDASeq EDASeq is a Bioconductor package to perform GC-Content Normalization for RNA-Seq Data.
  • GeneScissors GeneScissors.
  • SysCall SysCall is a classifier tool to identification and correction of systematic error in high-throughput sequence data.

Fusion genes/chimeras/translocation finders/structural variations[edit]

Genome arrangements result of diseases like cancer can produce aberrant genetic modifications like fusions or translocations. Identification of these modifications play important role in carcinogenesis studies.

Copy Number Variation identification[edit]

RNA-Seq simulators[edit]

These Simulators generate in silico reads and are a useful tool to compare and test the efficiency of algorithms developed to handle RNA-Seq data. Moreover, some of them make possible to analyse and model RNA-Seq protocols.

  • BEERS Simulator BEERS is formatted to mouse or human data, and paired-end reads sequenced on Illumina platform. Beers generates reads starting from a pool of gene models coming from different published annotation origins. Some genes are chosen randomly and afterwards are introduced deliberately errors (like indels, base changes and low quality tails), followed by construction of novel splice junctions.
  • dwgsim dwgsim.
  • Flux simulator Flux Simulator implements a computer pipeline simulation to mimic a RNA-Seq experiment. All component steps that influence RNA-Seq are taken into account (reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing) in the simulation. These steps present experimental attributes that can be measured, and the approximate experimental biases are captured. Flux Simulator allows joining each of these steps as modules to analyse different type of protocols. See also seqanswers/Flux.
  • rlsim rlsim is a software package for simulating RNA-seq library preparation with parameter estimation.
  • RSEM Read Simulator rsem-simulate-reads.
  • RNASeqReadSimulator RNASeqReadSimulator contains a set of simple Python scripts, command line driven. It generates random expression levels of transcripts (single or paired-end), equally simulates reads with a specific positional bias pattern and generates random errors from sequencing platforms.
  • RNA Seq Simulator RNA Seq Simulator.

Transcriptome assemblers[edit]

The transcriptome is the total population of RNAs expressed in one cell or group of cells, including non-coding and protein-coding RNAs. There are two types of approaches to assemble transcriptomes. Genome-guided methods use a reference genome (if possible a finished and high quality genome) as a template to align and assembling reads into transcripts. Genome-independent methods does not require a reference genome and are normally used when a genome is not available. In this case reads are assembled directly in transcripts.

Genome-Guided assemblers[edit]

Genome-Independent assemblers[edit]

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