IPCAPS.BIOC-package: IPCAPS.BIOC : Iterative Pruning to CApture Population...

In kridsadakorn/ipcaps.bioc: Iterative Pruning to Capture Population Structure

Description

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 (Intarapanich et al., 2009; Limpiti et al., 2011). The ipcaps involves an iterative process using multiple splits based on multivariate Gaussian mixture modeling of principal components and Clustering EM estimation as explained in Lebret et al. (2015). In each iteration, rough clusters and outliers are also identified using the function rubikclust() from the R package KRIS.

Details

The R package IPCAPS.BIOC requires the package KRIS.

Here is the list of functions in the R package IPCAPS.BIOC:

• export.groups

• get.node.info

• ipcaps

• save.eigenplots.html

• save.html

• save.plots.cluster.html

• save.plots.label.html

• save.plots

• top.discriminator

Moreover, here is the list of example datasets in the R package IPCAPS.BIOC:

• raw.data

• label

• PC

Author(s)

Maintainer: Kridsadakorn Chaichoompu [e-mail]

Authors:

• Kristel Van Steen

• Fentaw Abegaz

• Sissades Tongsima

• Philip Shaw

• Anavaj Sakuntabhai

• Luisa Pereira

• Alisa Wilantho

• Bertram Müller-Myhsok

References

Chaichoompu K, Abegaz F, Tongsima S, Shaw PJ, Sakuntabhai A, Pereira L, et al. IPCAPS: an R package for iterative pruning to capture population structure. Source Code Biol Med. 2019;14. doi:10.1186/s13029-019-0072-6.

Intarapanich, A., Shaw, P.J., Assawamakin, A., Wangkumhang, P., Ngamphiw, C., Chaichoompu, K., Piriyapongsa, J., and Tongsima, S. (2009). Iterative pruning PCA improves resolution of highly structured populations. BMC Bioinformatics 10, 382.

Lebret, R., Iovleff, S., Langrognet, F., Biernacki, C., Celeux, G., and Govaert, G. (2015). Rmixmod: TheRPackage of the Model-Based Unsupervised, Supervised, and Semi-Supervised ClassificationMixmodLibrary. J. Stat. Softw. 67.

Limpiti, T., Intarapanich, A., Assawamakin, A., Shaw, P.J., Wangkumhang, P., Piriyapongsa, J., Ngamphiw, C., and Tongsima, S. (2011). Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure. BMC Bioinformatics 12, 255.

See Also

Useful links:

• https://github.com/kridsadakorn/ipcaps

• Report bugs at https://github.com/kridsadakorn/ipcaps/issues

kridsadakorn/ipcaps.bioc documentation built on Jan. 22, 2020, 11:18 p.m.