Literature DB >> 22485116

Improving RNA-Seq Precision with MapAl.

Paweł P Labaj1, Bryan E Linggi, H Steven Wiley, David P Kreil.   

Abstract

With currently available RNA-Seq pipelines, expression estimates for most genes are very noisy. We here introduce MapAl, a tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. In the post-processing of RNA-Seq reads, it incorporates gene models already at the stage of read alignment, increasing the number of reliably measured known transcripts consistently by 50%. Adding genes identified de novo then allows a reliable assessment of double the total number of transcripts compared to other available pipelines. This substantial improvement is of general relevance: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not.

Entities:  

Keywords:  RNA-Seq; gene expression profiling; measurement precision; read mapping; reliability; splice-form discrimination; transcriptomics

Year:  2012        PMID: 22485116      PMCID: PMC3316937          DOI: 10.3389/fgene.2012.00028

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


  21 in total

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Journal:  Nat Methods       Date:  2010-09-12       Impact factor: 28.547

2.  Statistical inferences for isoform expression in RNA-Seq.

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Journal:  Bioinformatics       Date:  2009-02-25       Impact factor: 6.937

3.  Mapping and quantifying mammalian transcriptomes by RNA-Seq.

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Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

4.  Stem cell transcriptome profiling via massive-scale mRNA sequencing.

Authors:  Nicole Cloonan; Alistair R R Forrest; Gabriel Kolle; Brooke B A Gardiner; Geoffrey J Faulkner; Mellissa K Brown; Darrin F Taylor; Anita L Steptoe; Shivangi Wani; Graeme Bethel; Alan J Robertson; Andrew C Perkins; Stephen J Bruce; Clarence C Lee; Swati S Ranade; Heather E Peckham; Jonathan M Manning; Kevin J McKernan; Sean M Grimmond
Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

5.  Microindel detection in short-read sequence data.

Authors:  Peter Krawitz; Christian Rödelsperger; Marten Jäger; Luke Jostins; Sebastian Bauer; Peter N Robinson
Journal:  Bioinformatics       Date:  2010-02-09       Impact factor: 6.937

Review 6.  Exon recognition in vertebrate splicing.

Authors:  S M Berget
Journal:  J Biol Chem       Date:  1995-02-10       Impact factor: 5.157

7.  RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.

Authors:  Bo Li; Colin N Dewey
Journal:  BMC Bioinformatics       Date:  2011-08-04       Impact factor: 3.307

8.  Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation.

Authors:  Cole Trapnell; Brian A Williams; Geo Pertea; Ali Mortazavi; Gordon Kwan; Marijke J van Baren; Steven L Salzberg; Barbara J Wold; Lior Pachter
Journal:  Nat Biotechnol       Date:  2010-05-02       Impact factor: 54.908

9.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

10.  TopHat: discovering splice junctions with RNA-Seq.

Authors:  Cole Trapnell; Lior Pachter; Steven L Salzberg
Journal:  Bioinformatics       Date:  2009-03-16       Impact factor: 6.937

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  1 in total

1.  The genome of the rice planthopper egg parasitoid wasps Anagrus nilaparvatae casts light on the chemo- and mechanosensation in parasitism.

Authors:  Ying Ma; Zixiao Guo; Liyang Wang; Bingyang Wang; Tingfa Huang; Bingjie Tang; Guren Zhang; Qiang Zhou
Journal:  BMC Genomics       Date:  2022-07-28       Impact factor: 4.547

  1 in total

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