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 (≥ 3.2.4.0) |
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 |
Please use the canonical form https://CRAN.R-project.org/package=IPCAPS to link to this page.