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Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments
2016
BMC Bioinformatics
RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression
doi:10.1186/s12859-016-0994-9
pmid:27029470
pmcid:PMC4815167
fatcat:cj5kgy5qovbwvlx5o77olq45lq