The functional false discovery rate with applications to genomics.

TitleThe functional false discovery rate with applications to genomics.
Publication TypeJournal Article
Year of Publication2021
AuthorsChen, X, Robinson, DG, Storey, JD
Date Published2021 Jan 28
KeywordsAnimals, Gene Expression Profiling, Genetic Markers, Genomics, Mice, Probability, Saccharomyces cerevisiae

<p>The false discovery rate (FDR) measures the proportion of false discoveries among a set of hypothesis tests called significant. This quantity is typically estimated based on p-values or test statistics. In some scenarios, there is additional information available that may be used to more accurately estimate the FDR. We develop a new framework for formulating and estimating FDRs and q-values when an additional piece of information, which we call an "informative variable", is available. For a given test, the informative variable provides information about the prior probability a null hypothesis is true or the power of that particular test. The FDR is then treated as a function of this informative variable. We consider two applications in genomics. Our first application is a genetics of gene expression (eQTL) experiment in yeast where every genetic marker and gene expression trait pair are tested for associations. The informative variable in this case is the distance between each genetic marker and gene. Our second application is to detect differentially expressed genes in an RNA-seq study carried out in mice. The informative variable in this study is the per-gene read depth. The framework we develop is quite general, and it should be useful in a broad range of scientific applications.</p>

Alternate JournalBiostatistics
PubMed ID31135886
PubMed Central IDPMC7846131
Grant ListR01 HG002913 / HG / NHGRI NIH HHS / United States
R01 HG006448 / HG / NHGRI NIH HHS / United States
T32 HG003284 / HG / NHGRI NIH HHS / United States