Python API

Import admix-kit as:

import admix

Association testing

admix.assoc.marginal

Marginal association testing for one SNP at a time

Genetic correlation across local ancestry

Note

For genetic correlation analyis, because of involvement of multiple steps, it is recommended to use the command line interface admix genet-cor to perform the analysis. See here for details.

admix.cli.admix_grm	Calculate the admix GRM for a given pfile
admix.cli.admix_grm_merge	Merge multiple GRM matrices
admix.cli.genet_cor	Estimate genetic correlation

Polygenic scoring

admix.data.calc_partial_pgs

Given a vector of polygenic score weights, calculate polygenic scores with regard to every ancestry backgrounds for each individual.

Data structures: admix.Dataset

admix.Dataset

Data structure to contain genotype and local ancestry.

Simulation: admix.simulate

admix.simulate.admix_geno	Simulate admixed genotype
admix.simulate.quant_pheno	Simulate continuous phenotype of admixed individuals [continuous]
admix.simulate.binary_pheno	Simulate under liability threshold.
admix.simulate.quant_pheno_1pop	Simulate quantative phenotype for a single population [continuous]
admix.simulate.quant_pheno_grm	Simulate continuous phenotype of admixed individuals [continuous] using GRM

Data management: admix.data

admix.data.allele_per_anc	Get allele count per ancestry
admix.data.af_per_anc	Calculate allele frequency per ancestry

Input and output: admix.io

admix.io.read_dataset	Read a dataset from a directory.
admix.io.read_lanc	Read local ancestry with .lanc format
admix.io.read_rfmix	Assign local ancestry to a dataset.

External tools: admix.tools

admix.tools.plink2.lift_over

Lift over a plink file to another genome.

Plot: admix.plot

admix.plot.lanc	Plot local ancestry.
admix.plot.admixture	Plot admixture.
admix.plot.manhattan	Manhatton plot of p-values
admix.plot.qq	qq plot of p-values