Crandore Hub

rhcoclust

Robust Hierarchical Co-Clustering to Identify Significant Co-Cluster

Here we performs robust hierarchical co-clustering between row and column entities of a data matrix in absence and presence of outlying observations. It can be used to explore important co-clusters consisting of important samples and their regulatory significant features. Please see Hasan, Badsha and Mollah (2020) <doi:10.1101/2020.05.13.094946>.

Versions across snapshots

VersionRepositoryFileSize
2.0.0 rolling linux/jammy R-4.5 rhcoclust_2.0.0.tar.gz 206.7 KiB
2.0.0 rolling linux/noble R-4.5 rhcoclust_2.0.0.tar.gz 206.5 KiB
2.0.0 rolling source/ R- rhcoclust_2.0.0.tar.gz 165.5 KiB
2.0.0 latest linux/jammy R-4.5 rhcoclust_2.0.0.tar.gz 206.7 KiB
2.0.0 latest linux/noble R-4.5 rhcoclust_2.0.0.tar.gz 206.5 KiB
2.0.0 latest source/ R- rhcoclust_2.0.0.tar.gz 165.5 KiB
2.0.0 2026-04-26 source/ R- rhcoclust_2.0.0.tar.gz 165.5 KiB
2.0.0 2026-04-23 source/ R- rhcoclust_2.0.0.tar.gz 165.5 KiB
2.0.0 2026-04-09 windows/windows R-4.5 rhcoclust_2.0.0.zip 209.8 KiB
2.0.0 2025-04-20 source/ R- rhcoclust_2.0.0.tar.gz 165.5 KiB

Dependencies (latest)

Imports