Construction of a Pearson- and MIC-Based Co-expression Network to Identify Potential Cancer Genes.
Interdiscip Sci
; 14(1): 245-257, 2022 Mar.
Article
en En
| MEDLINE
| ID: mdl-34694561
ABSTRACT
The weighted gene co-expression network analysis (WGCNA) method constructs co-expressed gene modules based on the linear similarity between paired gene expressions. Linear correlations are the main form of similarity between genes, however, nonlinear correlations still existed and had always been ignored. We proposed a modified network analysis method, WGCNA-P + M, which combines Pearson's correlation coefficient and the maximum information coefficient (MIC) as the similarity measures to assess the linear and nonlinear correlations between genes, respectively. Taking two real datasets, GSE44861 and liver hepatocellular carcinoma (TCGA-LIHC), as examples, we compared the gene modules constructed by WGCNA-P + M and WGCNA from four perspectives the "Usefulness" score, GO enrichment analysis on genes in the gray module, prediction performance of the top hub gene, survival analysis and literature reports on different hub genes. The results showed that the modules obtained by WGCNA-P + M are more biological meaningful, the hub genes obtained from WGCNA-P + M have more potential cancer genes.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Carcinoma Hepatocelular
/
Neoplasias Hepáticas
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Interdiscip Sci
Asunto de la revista:
BIOLOGIA
Año:
2022
Tipo del documento:
Article
País de afiliación:
China