Gene co-expression network based on part mutual information for gene-to-gene relationship and gene-cancer correlation analysis.

ABSTRACT:

Background

Finding correlation patterns is an important goal of analyzing biological data. Currently available methods for correlation analysis mainly use non-direct associations, such as the Pearson correlation coefficient, and focus on the interpretation of networks at the level of modules. For biological objects such as genes, their collective function depends on pairwise gene-to-gene interactions. However, a large amount of redundant results from module level methods often necessitate further detailed analysis of gene interactions. New approaches of measuring direct associations among variables, such as the part mutual information (PMI), may help us better interpret the correlation pattern of biological data at the level of variable pairs.

Results

We use PMI to calculate

SUBMITTER: Jiang YH 

PROVIDER: S-EPMC9128248 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature