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GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data.
Bioinformatics. 2012 Aug 24;
Authors: Feng J, Meyer CA, Wang Q, Liu JS, Liu XS, Zhang Y
Abstract
MOTIVATION: RNA-seq has been widely used to transcriptome analysis to effectively measure gene expression levels. Although sequencing costs are rapidly decreasing, almost 70% of all the human RNA-seq samples in the Gene Expression Omnibus (GEO) do not have biological replicates and more unreplicated RNA-seq data were published than replicated RNA-seq data in 2011. Despite the large amount of single replicate studies, there is currently no satisfactory method for detecting differentially expressed genes when only a single biological replicate is available. RESULTS: We present the GFOLD (generalized fold change) algorithm to produce biologically meaningful rankings of differentially expressed genes from RNA-seq data. GFOLD assigns reliable statistics for expression changes based on the posterior distribution of log fold change. In this way GFOLD overcomes the shortcomings of p-value and fold change calculated by existing RNA-seq analysis methods and gives more stable and biological meaningful gene rankings when only a single biological replicate is available. AVAILABILITY: The open source C/C++ program is available at http://www.tongji.edu.cn/~zhanglab/GFOLD/index.html CONTACT: X. Shirley Liu - [email protected]; Yong Zhang - [email protected].
PMID: 22923299 [PubMed - as supplied by publisher]
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GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data.
Bioinformatics. 2012 Aug 24;
Authors: Feng J, Meyer CA, Wang Q, Liu JS, Liu XS, Zhang Y
Abstract
MOTIVATION: RNA-seq has been widely used to transcriptome analysis to effectively measure gene expression levels. Although sequencing costs are rapidly decreasing, almost 70% of all the human RNA-seq samples in the Gene Expression Omnibus (GEO) do not have biological replicates and more unreplicated RNA-seq data were published than replicated RNA-seq data in 2011. Despite the large amount of single replicate studies, there is currently no satisfactory method for detecting differentially expressed genes when only a single biological replicate is available. RESULTS: We present the GFOLD (generalized fold change) algorithm to produce biologically meaningful rankings of differentially expressed genes from RNA-seq data. GFOLD assigns reliable statistics for expression changes based on the posterior distribution of log fold change. In this way GFOLD overcomes the shortcomings of p-value and fold change calculated by existing RNA-seq analysis methods and gives more stable and biological meaningful gene rankings when only a single biological replicate is available. AVAILABILITY: The open source C/C++ program is available at http://www.tongji.edu.cn/~zhanglab/GFOLD/index.html CONTACT: X. Shirley Liu - [email protected]; Yong Zhang - [email protected].
PMID: 22923299 [PubMed - as supplied by publisher]
More...
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