- It can detect subgroups which show major differences and also moderate differences.
- It can detect subgroups with large sizes as well as with tiny sizes.
- It generates detailed HTML reports for the complete analysis.
Hierarchical consensus partitioning is part of the cola package (version >= 2.0.0). You can install it by:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("cola")The latest version can be installed directly from GitHub:
library(devtools)
install_github("jokergoo/cola")
Three lines of code to perfrom hierarchical consensus partitioning analysis:
mat = adjust_matrix(mat) # optional
rh = hierarchical_partition(mat, mc.cores = ...)
cola_report(rh, output_dir = ...)The documentation is included in the cola package: https://jokergoo.github.io/cola_vignettes/hierarchical.html
Following figure shows the hierarchy of the subgroups.
Following figure shows the signature genes.
MIT @ Zuguang Gu