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Topconfects: a package for confident effect sizes in differential expression analysis provides a more biologically useful ranked gene list

Author:
Harrison, Paul F., Pattison, Andrew D., Powell, David R., Beilharz, Traude H.
Source:
Genome biology 2019 v.20 no.1 pp. 67
ISSN:
1474-760X
Subject:
breast neoplasms, data collection, gene expression regulation, genes
Abstract:
Differential gene expression analysis may discover a set of genes too large to easily investigate, so a means of ranking genes by biological interest level is desired. p values are frequently abused for this purpose. As an alternative, we propose a method of ranking by confidence bounds on the log fold change, based on the previously developed TREAT test. These confidence bounds provide guaranteed false discovery rate and false coverage-statement rate control. When applied to a breast cancer dataset, the top-ranked genes by Topconfects emphasize markedly different biological processes compared to the top-ranked genes by p value.
Agid:
6353372