| 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. |