Iterative Pruning to Capture Population Structure

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Documentation for package ‘IPCAPS’ version 1.1.8

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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 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 scatter plots which all data points are highlighted by IPCAPS clusters
save.plots.label.html Generate HTML file for scatter plots which data points are highlighted by given labels
top.discriminator Detecting top discriminators between two groups