LDadmix

Estimate the haplotype frequencies and LD in the ancestral populations of admixed samples.

installation

# pull code from github and enter directory
git clone https://github.com/rwaples/LDadmix.git
cd LDadmix

# if needed, create a conda environment for LDadmix
conda env create -f ./LDadmix.conda.yml
conda activate LDadmix

run LDadmix on the included example data set

# from LDadmix directory
python3 ./ancLD/ancLD.py -G ./example/example_1 -O ./example/example_1.out.gz

usage

python3 ancLD.py --help

requirements

tested on Python 3.6

python packages

• numpy
• scipy
• pandas
• pandas-plink
• numba

output format

Tab-delimited text file, one line per pair of loci per population. Output will be gzipped (*.gz) if the path ends in ".gz". Output files can get large, compression is recommended.

• i1, i2 : index of locus[1/2] within chromosome (zero-indexed)
• locus1, locus2 : name of locus[1/2], taken from the .bim file
• CHR : chromosome
• bp_dist : basepair distance between the locus1 and locus2
• genetic_dist : genetic distance between the locus1 and locus2
• non_missing : the number of individuals with non-missing genotypes
• pop : population (based on position in Q file) (one-indexed)
• iter : number of EM iterations
• logLike : (log)likelihood of the data at the termination of the EM
• flag : nonzero if either locus has minor allele frequency < 0.05
• Hap00 : frequency of the 0_0 haplotype
• Hap01 : frequency of the 0_1 haplotype
• Hap10 : frequency of the 1_0 haplotype
• Hap11 : frequency of the 1_1 haplotype
• r2 : r^2 value, based on the haplotype frequencies
• D : D value, based on the haplotype frequencies
• Dprime : D' value, based on the haplotype frequencies = [abs(D/Dmax)]
• p1 : allele frequency at locus1, based on the haplotype frequencies
• p2 : allele frequency at locus2, based on the haplotype frequencies