Table 1 Summary of PyAGH’s functions
From: PyAGH: a python package to fast construct kinship matrices based on different levels of omic data
Category | Function | Description |
|---|---|---|
Pedigree | sortPed() | Sort the pedigree data according to the correct birth date of individuals and check for various errors in the pedigree like offspring born before its parents, same offspring have different parents, loop in pedigree and etc |
selectPed() | Select pedigree based on specific individuals and generations | |
makeA() | Construct kinship matrix based on pedigree information for additive effect. Option to use sparse matrix for memory saving | |
makeD() | Construct kinship matrix based on pedigree information for dominant effect. Option to use multithreading when there are multiple CPU | |
Genome | makeG() | Construct kinship matrix based on genotype data for additive effect. Option to use different methods |
makeG_inter() | Construct kinship matrix based on genotype data for dominance and epistatic effect. Option to use multithreading | |
makeH() | Combine information of pedigree and genotypes to construct kinship matrix for both genotyped and ungenotyped individuals | |
Microbiome | makeM() | Construct kinship matrix based on microbiome data |
Transcriptome | makeT() | Construct kinship matrix based on transcriptome data |
Composition analysis and visualization | coefKinship() | Calculate the ancestry coefficients using kinship matrix |
coefInbreeding() | Calculate the inbreeding coefficients using kinship matrix | |
cluster() | Cluster analysis of the kinship matrix and plot the result | |
pca() | Principal component analysis of kinship matrix and plot the result | |
heat() | Plot the heatmap of a kinship matrix | |
gragh() | Plot family tree tracing back up to three generations of an individual |