Testing significance relative to a fold-change threshold is a TREAT
- Author(s)
- McCarthy, DJ; Smyth, GK;
- Details
- Publication Year 2009-03-15,Volume 25,Issue #6,Page 765-771
- Journal Title
- BIOINFORMATICS
- Publication Type
- Journal Article
- Abstract
- Motivation: Statistical methods are used to test for the differential expression of genes in microarray experiments. The most widely used methods successfully test whether the true differential expression is different from zero, but give no assurance that the differences found are large enough to be biologically meaningful. Results: We present a method, t-tests relative to a threshold (TREAT), that allows researchers to test formally the hypothesis (with associated p-values) that the differential expression in a microarray experiment is greater than a given (biologically meaningful) threshold. We have evaluated the method using simulated data, a dataset from a quality control experiment for microarrays and data from a biological experiment investigating histone deacetylase inhibitors. When the magnitude of differential expression is taken into account, TREAT improves upon the false discovery rate of existing methods and identifies more biologically relevant genes.
- Publisher
- OXFORD UNIV PRESS
- Keywords
- SMALL MICROARRAY EXPERIMENTS; GENE-EXPRESSION
- Publisher's Version
- https://doi.org/10.1093/bioinformatics/btp053
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2009-03-15 12:00:00