# Iterative Pruning to Capture Population Structure

## Documentation for package ‘IPCAPS’ version 1.1.5

- DESCRIPTION file.

## Help Pages

cal.eigen.fit | (Internal function) Calculae a vector of EigenFit values, internally used for parallelization
check.stopping | (Internal function) Check whether the IPCAPS process meets the stopping criterion.
clustering | (Internal function) Perform the clustering process of IPCAPS
clustering.mode | (Internal function) Select a clustering method to be used for the IPCAPS process.
diff.eigen.fit | (Internal function) Calculate a vector of different values from a vector of EigenFit values, internally used for parallelization
diff.xy | (Internal function) Check the different value of X and Y, internally used for parallelization
do.glm | (Internal function) Perform regression models, internally used for parallelization
export.groups | Export the IPCAPS result in to a text file
get.node.info | Get the information for specified node
ipcaps | Perform unsupervised clustering to capture population structure based on iterative pruning
label | Synthetic dataset containing population labels for the dataset 'raw.data'
output.template | (Internal object) The HTML output template for IPCAPS
pasre.categorical.data | (Internal function) Manipulate categorical input files
PC | Synthetic dataset containing the top 10 principal components (PC) from the dataset 'raw.data'
postprocess | (Internal function) Perform the post-processing step of IPCAPS
preprocess | (Internal function) Perform the pre-processing step of IPCAPS
process.each.node | (Internal function) Perform the iterative process for each node
raw.data | Synthetic dataset containing single nucleotide polymorphisms (SNP)
replace.missing | (Internal function) Replace missing values by specified values, internally used for parallelization
save.eigenplots.html | Generate HTML file for EigenFit plots
save.html | Generate HTML file for clustering result in text mode
save.plots | Workflow to generate HTML files for all kinds of plots
save.plots.cluster.html | Generate HTML file for scratter plots highlighting data points by IPCAPS clusters
save.plots.label.html | Generate HTML file for scratter plots highlighting data points by given labels
top.discriminator | Detecting top discriminators between two groups