The R package IPCAPS
is an unsupervised clustering
algorithm based on iterative pruning to capture 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 by
Intarapanich et al. (2009) <doi: 10.1186/1471-2105-10-382> and
Limpiti et al. (2011)<doi: 10.1186/1471-2105-12-255>. The IPCAPS
involves an iterative process using multiple splits based on
multivariate Gaussian mixture modeling of principal components and
Clustering EM estimation as in Lebret et al. (2015). In each iteration,
rough clusters and outliers are also identified using the function
rubikclust()
from the R package KRIS
.
The R package IPCAPS
requires stats
,
utils
, graphics
, grDevices
,
MASS
, Matrix
, expm
,
KRIS
, fpc
, LPCM
,
apcluster
, Rmixmod
.
Here is the list of functions in the R package
IPCAPS
:
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
:
label
PC
raw.data
Lastly, here is the list of example data files included in the
directory extdata
of IPCAPS
:
ipcaps_example.bed
ipcaps_example.bim
ipcaps_example.fam
ipcaps_example_PC10.txt.gz
ipcaps_example_individuals.txt.gz
ipcapsS_example_rowVar_colInd.txt.gz
ipcaps_example.rda
Install the released version of IPCAPS
from CRAN:
install.packages("IPCAPS")
The source codes in this package include the Roxgen’s syntax. If
there is a problem for generating the RD files (facing some errors)
using RStudio (Build > Document), try to use
roxygen2::roxygenise()
instead of Build >
Document from the menu. Alternatively, install the package
devtools
, then enable RStudio to use the functions from
devtools
(check Build > Configure Build Tools… >
use devtools package functions if available) or run
devtools::document()
in the console.
When facing error for testthat
, try to update the
package testthat
and add Suggests: testthat
in
DESCRIPTION file.
Check the submission using R CMD check --as-cran
and a
current version of r-devel, as mandated by the CRAN Repository Policy.
(You could do so using the win-builder service at
http://win-builder.r-project.org)
Check downstream dependencies with
devtools::revdep_check()
Edit ~/.profile, ~/.bash_profile or ~/.bashrc, then add
export LANG=en_US.UTF-8
export LC_ALL=en_US.UTF-8
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