DIME: R-package for identifying differential ChIP-seq based on an ensemble of mixture models

被引：17

作者：

Taslim, Cenny ^{[1
,2
]}

Huang, Tim ^{[2
]}

Lin, Shili ^{[1
]}

机构：

[1] Ohio State Univ, Dept Stat, Columbus, OH 43210 USA

[2] Ohio State Univ, Dept Mol Virol Immunol & Med Genet, Columbus, OH 43210 USA

来源：

BIOINFORMATICS | 2011年 / 27卷 / 11期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1093/bioinformatics/btr165

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Differential Identification using Mixtures Ensemble ( DIME) is a package for identification of biologically significant differential binding sites between two conditions using ChIP-seq data. It considers a collection of finite mixture models combined with a false discovery rate (FDR) criterion to find statistically significant regions. This leads to a more reliable assessment of differential binding sites based on a statistical approach. In addition to ChIP-seq, DIME is also applicable to data from other high-throughput platforms.

引用

页码：1569 / 1570

页数：2

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