Package: IPCAPS 1.1.8
Kridsadakorn Chaichoompu
IPCAPS: Iterative Pruning to Capture Population Structure
An unsupervised clustering algorithm based on iterative pruning is for capturing population structure. This version supports ordinal data which can be applied directly to SNP data to identify fine-level population structure and it is built on the iterative pruning Principal Component Analysis ('ipPCA') algorithm as explained in Intarapanich et al. (2009) <doi:10.1186/1471-2105-10-382>. The 'IPCAPS' involves an iterative process using multiple splits based on multivariate Gaussian mixture modeling of principal components and 'Expectation-Maximization' clustering as explained in Lebret et al. (2015) <doi:10.18637/jss.v067.i06>. In each iteration, rough clusters and outliers are also identified using the function rubikclust() from the R package 'KRIS'.
Authors:
IPCAPS_1.1.8.tar.gz
IPCAPS_1.1.8.tar.gz(r-4.5-noble)IPCAPS_1.1.8.tar.gz(r-4.4-noble)
IPCAPS_1.1.8.tgz(r-4.4-emscripten)IPCAPS_1.1.8.tgz(r-4.3-emscripten)
IPCAPS.pdf |IPCAPS.html✨
IPCAPS/json (API)
NEWS
# Install 'IPCAPS' in R: |
install.packages('IPCAPS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:38cbcceb25. Checks:OK: 1 ERROR: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 25 2024 |
R-4.5-linux | ERROR | Nov 25 2024 |
Exports:export.groupsget.node.infoipcapssave.eigenplots.htmlsave.htmlsave.plotssave.plots.cluster.htmlsave.plots.label.htmltop.discriminator
Dependencies:apclusterclassclusterDEoptimRdiptestexpmflexmixfpckernlabKRISlatticeLPCMMASSMatrixmclustmodeltoolsnnetprabclusrARPACKRcppRcppEigenRmixmodrobustbaseRSpectra