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


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.

SUBMITTER: Harrison PF 

PROVIDER: S-EPMC6437914 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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

Harrison Paul F PF   Pattison Andrew D AD   Powell David R DR   Beilharz Traude H TH  

Genome biology 20190328 1


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 dat  ...[more]

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