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An integrated approach to identify bimodal genes associated with prognosis in cancer.

ABSTRACT: Bimodal gene expression (where a gene expression distribution has two maxima) is associated with phenotypic diversity in different biological systems. A critical issue, thus, is the integration of expression and phenotype data to identify genuine associations. Here, we developed tools that allow both: i) the identification of genes with bimodal gene expression and ii) their association with prognosis in cancer patients from The Cancer Genome Atlas (TCGA). Bimodality was observed for 554 genes in expression data from 25 tumor types. Furthermore, 96 of these genes presented different prognosis when patients belonging to the two expression peaks were compared. The software to execute the method and the corresponding documentation are available at the Data access section.

SUBMITTER: Justino JR

PROVIDER: S-EPMC8495773 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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An integrated approach to identify bimodal genes associated with prognosis in câncer.

Justino Josivan Ribeiro JR Reis Clovis Ferreira Dos CFD Fonseca Andre Luis AL Souza Sandro Jose de SJ Stransky Beatriz B

Genetics and molecular biology 20211004 3

Bimodal gene expression (where a gene expression distribution has two maxima) is associated with phenotypic diversity in different biological systems. A critical issue, thus, is the integration of expression and phenotype data to identify genuine associations. Here, we developed tools that allow both: i) the identification of genes with bimodal gene expression and ii) their association with prognosis in cancer patients from The Cancer Genome Atlas (TCGA). Bimodality was observed for 554 genes in ...[more]

PMID: 34617951

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