Differential expression analysis for sequence count data

被引：10049

作者：

Anders, Simon ^{[1
]}

Huber, Wolfgang ^{[1
]}

机构：

[1] European Mol Biol Lab, D-69117 Heidelberg, Germany

来源：

GENOME BIOLOGY | 2010年 / 11卷 / 10期

关键词：

NEGATIVE BINOMIAL DISPERSION; RNA-SEQ; BIOCONDUCTOR; PACKAGE;

D O I：

10.1186/gb-2010-11-10-r106

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：

High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.

引用

页数：12

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