SEQanswers

Go Back   SEQanswers > Literature Watch



Similar Threads
Thread Thread Starter Forum Replies Last Post
RNA-Seq: A new approach to bias correction in RNA-Seq. Newsbot! Literature Watch 0 01-31-2012 03:00 AM
RNA-Seq: Overview of available methods for diverse RNA-Seq data analyses. Newsbot! Literature Watch 0 01-10-2012 04:00 AM
RNA-Seq: Full-length transcriptome assembly from RNA-Seq data without a reference gen Newsbot! Literature Watch 7 10-26-2011 05:37 AM
RNA-Seq: deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data. Newsbot! Literature Watch 0 06-01-2011 02:40 AM
Transcript length bias in RNA-seq data confounds systems biology. NGSfan Literature Watch 1 05-12-2009 03:35 PM

Reply
 
Thread Tools
Old 01-22-2011, 02:02 AM   #1
Newsbot!
RSS Posting Maniac
 

Join Date: Feb 2008
Posts: 1,439
Default RNA-Seq: Length Bias Correction for RNA-seq Data in Gene Set Analyses.

Syndicated from PubMed RSS Feeds

Length Bias Correction for RNA-seq Data in Gene Set Analyses.

Bioinformatics. 2011 Jan 19;

Authors: Gao L, Fang Z, Zhang K, Zhi D, Cui X

MOTIVATION: Next-generation sequencing technology is being rapidly applied to quantifying transcripts (RNA-seq). However, due to the unique properties of the RNA-seq data, the differential expression of longer transcripts is more likely to be identified than that of shorter transcripts with the same effect size. This bias complicates the downstream gene set analysis (GSA) because the methods for GSA previously developed for microarray data are based on the assumption that genes with same effect size have equal probability (power) to be identified as significantly differentially expressed. Since transcript length is not related to gene expression, adjusting for such length dependency in GSA becomes necessary. RESULTS: In this paper, we proposed two approaches for transcript-length adjustment for analyses based on Poisson models: 1) At individual gene level, we adjusted each gene's test statistic using the square root of transcript length followed by testing for gene set using the Wilcoxon Rank-Sum test. 2) At gene-set level, we adjusted the null distribution for the Fisher's exact test by weighting the identification probability of each gene using the square root of its transcript length. We evaluated these two approaches using simulations and a real dataset, and showed that these methods can effectively reduce the transcript-length biases. The top ranked GO terms obtained from the proposed adjustments show more overlaps with the microarray results. AVAILABILITY: R scripts are at http://www.soph.uab.edu/Statgenetics.../XCui/r-codes/ CONTACT: [email protected].

PMID: 21252076 [PubMed - as supplied by publisher]



More...
Newsbot! is offline   Reply With Quote
Reply

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off




All times are GMT -8. The time now is 07:54 PM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2018, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO