Kernel Learning Integrative Clustering
Overview
Kernel Learning Integrative Clustering (KLIC) is an algorithm that allows to combine multiple kernels, each representing a different measure of the similarity between a set of observations. The contribution of each kernel on the final clustering is weighted according to the amount of information carried by it. As well as providing the functions required to perform the kernel-based clustering, this package also allows the user to simply give the data as input: the kernels are then built using consensus clustering. Different strategies to choose the best number of clusters are also available. For further details please see Cabassi and Kirk (2020) doi:10.1093/bioinformatics/btaa593.
Install
Health
CRAN check results are not tracked yet.
- NOTE11 OK, 2 NOTE2026-06-09
- ERROR11 OK, 1 NOTE, 1 ERROR2026-06-08
- NOTE11 OK, 2 NOTE2026-05-02
- ERROR9 OK, 2 NOTE, 1 ERROR2026-04-25
- NOTE9 OK, 5 NOTE2026-03-10
Documentation
- Help pages
- 7
- Examples that run
- 100%7 run in a plain check (3 of them under a condition)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 71%
Downloads
Dependencies
Code & Tests
Datasets
People & History
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- archivedRemoved from CRAN2026-06-11email to the maintainer is undeliverable
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.0.42020-07-06 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 1.0.22020-04-03
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2020-04-03
- Total releases
- 2 / 6 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 1.4 MB
Cite
Cite this package
Run in R for the authors' entry:
citation("klic")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/bioinformatics/btaa593.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.