Haplotypes

Overall description: Perform haplotype calling, run QC across various metrics, convert files, perform demographic inference, perform IBD mapping

Pipeline Map

1.) Phase

2.) Infer shared haplotypes

3.) Perform haplotype QC

4.) Infer demographic history from haplotype sharing

5.) Perform IBD mapping for traits of interest

1.) Phase

A number of phasing options are available, for example BEAGLE, SHAPEIT, and HAPI-UR. Beagle has been around the longest and was considered the gold standard for improvement. SHAPEIT made substantial computational and accuracy gains for intermediate sample sizes (~100s to 1000s). HAPI-UR is more accurate than SHAPEIT on larger datasets (5000s-10000s). After phasing the data, convert it so that haplotypes can be inferred.

HAPI-UR running notes

• Indels break it. Ref/alt alleles must have a length no longer than 1 character
• Add genetic position for more reliable inference. If first genetic position is 0.0, it will try to set genetic from physical positions. Instead, set it to a very small number (e.g. 1e-5).

Example to add genetic position from Oxford recombination maps:

python makeMap.py \
--chr 22 \
--genmap genetic_map_chr22_combined_b37.txt \
--bim myFile.bim \
--out myFile.newbim

Convert phased haplotypes to format for inferring shared IBD

Example from HAPI-UR to RefinedIBD for haplotype inference:

python hapiur2vcf.py \
--phgeno dbs_1-10_pchip-qc_hardintersect_chr22_3x.phgeno \
--phind dbs_1-10_pchip-qc_hardintersect_chr22_3x.phind \
--phsnp dbs_1-10_pchip-qc_hardintersect_chr22_3x.phsnp \
--out dbs_1-10_pchip-qc_hardintersect_chr22_3x.vcf.gz

2.) Infer shared haplotypes

There are several software packages available for calling shared haplotypes, including e.g. GERMLINE and BEAGLE (i.e. RefinedIBD)