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

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.

摘要 双峰基因表达（Bimodal gene expression，即基因表达分布存在两个峰值）与多种生物系统中的表型多样性密切相关。因此，整合表达数据与表型数据以挖掘真实的关联关系，成为一项关键研究课题。本研究开发了可同时实现以下两项任务的工具：一是鉴定存在双峰基因表达的基因；二是挖掘这些基因与来自癌症基因组图谱（The Cancer Genome Atlas，TCGA）的癌症患者预后之间的关联。在25种肿瘤类型的表达数据中，共鉴定出554个存在双峰表达特征的基因。此外，当对比两个表达峰值对应的患者群体时，其中96个基因表现出与患者预后的显著差异关联。本研究方法对应的执行软件及相关文档可在数据获取板块获取。