SEQanswers

Go Back   SEQanswers > Literature Watch



Similar Threads
Thread Thread Starter Forum Replies Last Post
RNA-Seq: High-Throughput Illumina Strand-Specific RNA Sequencing Library Preparation. Newsbot! Literature Watch 1 01-21-2013 11:48 PM
PubMed: Barcoding bias in high-throughput multiplex sequencing of miRNA. Newsbot! Literature Watch 0 01-04-2012 02:10 AM
RNA-Seq: Personalized oncology through integrative high-throughput sequencing: a pilo Newsbot! Literature Watch 0 12-03-2011 02:40 AM
ChIP-Seq: Systematic bias in high-throughput sequencing data and its correction by BE Newsbot! Literature Watch 0 06-08-2011 02:50 AM
RNA-Seq: Improving RNA-Seq expression estimates by correcting for fragment bias. Newsbot! Literature Watch 0 03-18-2011 02:00 AM

Reply
 
Thread Tools
Old 02-11-2012, 02:00 AM   #1
Newsbot!
RSS Posting Maniac
 

Join Date: Feb 2008
Posts: 1,443
Default RNA-Seq: Summarizing and correcting the GC content bias in high-throughput sequencing

Syndicated from PubMed RSS Feeds

Summarizing and correcting the GC content bias in high-throughput sequencing.

Nucleic Acids Res. 2012 Feb 9;

Authors: Benjamini Y, Speed TP

Abstract
GC content bias describes the dependence between fragment count (read coverage) and GC content found in Illumina sequencing data. This bias can dominate the signal of interest for analyses that focus on measuring fragment abundance within a genome, such as copy number estimation (DNA-seq). The bias is not consistent between samples; and there is no consensus as to the best methods to remove it in a single sample. We analyze regularities in the GC bias patterns, and find a compact description for this unimodal curve family. It is the GC content of the full DNA fragment, not only the sequenced read, that most influences fragment count. This GC effect is unimodal: both GC-rich fragments and AT-rich fragments are underrepresented in the sequencing results. This empirical evidence strengthens the hypothesis that PCR is the most important cause of the GC bias. We propose a model that produces predictions at the base pair level, allowing strand-specific GC-effect correction regardless of the downstream smoothing or binning. These GC modeling considerations can inform other high-throughput sequencing analyses such as ChIP-seq and RNA-seq.


PMID: 22323520 [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 01:51 AM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2020, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO