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: |
1.1.8 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats, utils, graphics, grDevices, MASS, Matrix, expm, KRIS, fpc, LPCM, apcluster, Rmixmod |
| Suggests: |
testthat |
| Published: |
2021-01-25 |
| DOI: |
10.32614/CRAN.package.IPCAPS |
| 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 |