Reference

All functions
cal.pc.linear()	Calculate linear principal component analysis (PCA) from numeric data and Single-nucleotide polymorphism (SNP) dataset
cal.pc.projection()	Calculate linear principal component analysis (PCA) with a projection method for Single-nucleotide polymorphism (SNP) dataset.
fst.each.snp.hudson()	Calculate the fixation index (Fst) for all SNPs between two groups of individuals from Single-nucleotide polymorphism (SNP)
fst.hudson()	Calculate the average fixation index (Fst) between two groups of individuals from Single-nucleotide polymorphism (SNP)
plot3views()	Create scatter plots in three views.
read.bed()	Read the binary PLINK format (BED, BIM, and FAM)
replace.missing()	(Internal) Replace missing values with other values,internally used for parallelization
rubikclust()	Unsupervised clustering to detect rough structures and outliers.
example_SNP	Synthetic dataset containing population labels for the dataset simsnp.
example_SNP	Synthetic dataset containing single nucleotide polymorphisms (SNP)
write.bed()	Write a list of SNP object to the binary PLINK format (BED, BIM, and FAM)
xxt()	Calculate matrix multipication between a matrix and its transpose for large data.