期刊
BIOINFORMATICS
卷 24, 期 12, 页码 1461-1462出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btn209
关键词
-
False discovery rate (FDR) methodologies are essential in the study of high-dimensional genomic and proteomic data. The R package 'fdrtool' facilitates such analyses by offering a comprehensive set of procedures for FDR estimation. Its distinctive features include: (i) many different types of test statistics are allowed as input data, such as P-values, z-scores, correlations and t-scores; (ii) simultaneously, both local FDR and tail area-based FDR values are estimated for all test statistics and (iii) empirical null models are fit where possible, thereby taking account of potential over- or under-dispersion of the theoretical null. In addition, 'fdrtool' provides readily interpretable graphical output, and can be applied to very large scale (in the order of millions of hypotheses) multiple testing problems. Consequently, 'fdrtool' implements a flexible FDR estimation scheme that is unified across different test statistics and variants of FDR.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据