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'.

Version: 1.1.5
Depends: R (≥
Imports: stats, utils, graphics, grDevices, MASS, Matrix, expm, KRIS, fpc, LPCM, apcluster, Rmixmod
Suggests: testthat
Published: 2018-06-14
Author: Kridsadakorn Chaichoompu [aut, cre], Kristel Van Steen [aut], Fentaw Abegaz [aut], Sissades Tongsima [aut], Philip Shaw [aut], Anavaj Sakuntabhai [aut], Luisa Pereira [aut]
Maintainer: Kridsadakorn Chaichoompu <kridsadakorn at biostatgen.org>
BugReports: https://gitlab.com/kris.ccp/ipcaps/issues
License: GPL-3
URL: https://gitlab.com/kris.ccp/ipcaps
NeedsCompilation: no
Citation: IPCAPS citation info
Materials: README NEWS
CRAN checks: IPCAPS results


Reference manual: IPCAPS.pdf
Package source: IPCAPS_1.1.5.tar.gz
Windows binaries: r-devel: IPCAPS_1.1.5.zip, r-release: IPCAPS_1.1.5.zip, r-oldrel: IPCAPS_1.1.5.zip
OS X binaries: r-release: IPCAPS_1.1.5.tgz, r-oldrel: IPCAPS_1.1.5.tgz


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