Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data
Transcriptomics Dataset
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General Information
AccessionGSE49712
TitleComprehensive evaluation of differential gene expression analysis methods for RNA-seq data
DescriptionA large number of computational methods have been recently developed for analyzing differential gene expression (DE) in RNA-seq data. We report on a comprehensive evaluation of the commonly used DE methods using the SEQC benchmark data set and data from ENCODE project. We evaluated a number of key features including: normalization, accuracy of DE detection and DE analysis when one condition has no detectable expression. We found significant differences among the methods. Furthermore, computational methods designed for DE detection from expression array data perform comparably to methods customized for RNA-seq. Most importantly, our results demonstrate that increasing the number of replicate samples significantly improves detection power over increased sequencing depth.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49712
RepositoryGene Expression Omnibus
Tools used to analyze the dataset
Dataset Accession
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Canned Analyses generated with the dataset
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Tool Name
Interactive heatmap visualization of RNA-seq dataset GSE49712
ARCHS4, Clustergrammer
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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