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. |
sample_labels |
Synthetic dataset containing population labels for the dataset simsnp. |
simsnp |
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. |