cwgcna - v1.0.0

WGCNA (weighted gene co-expression network analysis) is a very useful tool for identifying co-expressed gene modules and detecting their correlations to phenotypic traits. Here, we explored more possibilities about it and developed the R package CWGCNA (causal WGCNA), which works from the traditional WGCNA pipeline but mines more information. It couples a mediation model with WGCNA, so the causal relationships among the WGCNA modules, module features, and phenotypes can be identified, demonstrating whether the module change causes the phenotype change or vice versa. After that, when annotating the module gene set functions, CWGCNA uses a novel network-based method, considering the modules’ topological structures and capturing their influence on the gene set functions. In addition to these biological explorations, CWGCNA also contains a machine learning section to perform clustering and classification on multi-omics data, given the increasing popularity of this kind of data. Some basic functions, such as differential feature identification, are also available in our package. Full Changelog: https://github.com/yuabrahamliu/CWGCNA/commits/v1.0.0

- R
Published by yuabrahamliu almost 2 years ago