Evaluation of read count based RNAseq analysis methods
作者： Yan Guo , Chung-I Li , Fei Ye , Yu Shyr
DOI: 10.1186/1471-2164-14-S8-S2
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摘要: RNAseq technology is replacing microarray as the tool of choice for gene expression profiling. While providing much richer data than microarray, analysis has been more challenging. To date, there not a consensus on best approach conducting robust analysis. In this study, we designed thorough experiment to evaluate six read count-based methods (DESeq, DEGseq, edgeR, NBPSeq, TSPM and baySeq) using both real simulated data. We found produce similar fold changes reasonable overlapping differentially expressed genes based p-values. However, all suffer from over-sensitivity. Based evaluation runtime area under receiver operating characteristic curve (AUC-ROC) data, that edgeR achieves better balance between speed accuracy other methods.
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