Modeling non-uniformity in short-read rates in RNA-Seq data

被引：134

作者：

Li, Jun ^{[1
]}

Jiang, Hui ^{[1
,2
]}

Wong, Wing Hung ^{[1
,3
]}

机构：

[1] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

[2] Stanford Genome Technol Ctr, Palo Alto, CA 94304 USA

[3] Stanford Univ, Dept Hlth Res & Policy, Stanford, CA 94305 USA

来源：

GENOME BIOLOGY | 2010年 / 11卷 / 05期

基金：

美国国家科学基金会;

关键词：

GENE-EXPRESSION; TRANSCRIPTOME; MICROARRAY; GENOME; ARRAYS; CHIP;

D O I：

10.1186/gb-2010-11-5-r50

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

After mapping, RNA-Seq data can be summarized by a sequence of read counts commonly modeled as Poisson variables with constant rates along each transcript, which actually fit data poorly. We suggest using variable rates for different positions, and propose two models to predict these rates based on local sequences. These models explain more than 50% of the variations and can lead to improved estimates of gene and isoform expressions for both Illumina and Applied Biosystems data.

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页数：11

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