| Name : R-hierBipartite
| |
| Version : 0.0.2
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.13
| Date : 2024-06-14 11:19:50
|
| Group : Development/Libraries/Other
| Source RPM : R-hierBipartite-0.0.2-lp153.1.13.src.rpm
|
| Size : 1.86 MB
| |
| Packager : (none)
| |
| Summary : Bipartite Graph-Based Hierarchical Clustering
|
Description :
Bipartite graph-based hierarchical clustering, developed for
pharmacogenomic datasets and datasets sharing the same data structure.
The goal is to construct a hierarchical clustering of groups of samples
based on association patterns between two sets of variables. In the
context of pharmacogenomic datasets, the samples are cell lines, and
the two sets of variables are typically expression levels and drug
sensitivity values. For this method, sparse canonical correlation
analysis from Lee, W., Lee, D., Lee, Y. and Pawitan, Y. (2011)
< doi:10.2202/1544-6115.1638> is first applied to extract association
patterns for each group of samples. Then, a nuclear norm-based
dissimilarity measure is used to construct a dissimilarity matrix
between groups based on the extracted associations. Finally,
hierarchical clustering is applied.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
