Bon-EV: an improved multiple testing procedure for controlling false discovery rates

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• 作者：Dongmei Li ; Zidian Xie ; Martin Zand ; Thomas Fogg ; Timothy Dye
• 关键词：Multiple testing procedure ; FDR ; Power ; Stability ; RNA ; Seq
• 刊名：BMC Bioinformatics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：18
• 期：1
• 全文大小：645KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105
• 卷排序：18

文摘

BackgroundStability of multiple testing procedures, defined as the standard deviation of total number of discoveries, can be used as an indicator of variability of multiple testing procedures. Improving stability of multiple testing procedures can help to increase the consistency of findings from replicated experiments. Benjamini-Hochberg’s and Storey’s q-value procedures are two commonly used multiple testing procedures for controlling false discoveries in genomic studies. Storey’s q-value procedure has higher power and lower stability than Benjamini-Hochberg’s procedure. To improve upon the stability of Storey’s q-value procedure and maintain its high power in genomic data analysis, we propose a new multiple testing procedure, named Bon-EV, to control false discovery rate (FDR) based on Bonferroni’s approach.