Justino Josivan Ribeiro, Reis Clovis Ferreira Dos, Fonseca Andre Luis, Souza Sandro Jose de, Stransky Beatriz
Universidade Federal do Rio Grande do Norte (UFRN), Metrópole Digital, Centro Multiusuário de Bioinformática, Natal, RN, Brazil.
Universidade Federal de Rondônia, Departamento de Matemática e Estatística, Ji-Parana, RO, Brazil.
Genet Mol Biol. 2021 Oct 4;44(3):e20210109. doi: 10.1590/1678-4685-GMB-2021-0109. eCollection 2021.
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.
双峰基因表达（即基因表达分布有两个最大值）与不同生物系统中的表型多样性相关。因此，一个关键问题是整合表达数据和表型数据以识别真正的关联。在此，我们开发了两种工具：i）识别具有双峰基因表达的基因；ii）将这些基因与来自癌症基因组图谱（TCGA）的癌症患者的预后相关联。在来自25种肿瘤类型的表达数据中观察到554个基因存在双峰现象。此外，当比较属于两个表达峰值的患者时，这些基因中有96个呈现出不同的预后。执行该方法的软件及相应文档可在数据访问部分获取。
