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aou_gwas

Code for the All-x-All AoU project.

Project Overview

Description

GWAS and RVAS on the AoU data.

Contributors

Analyses

Notes on running jobs with Hail Query-on-Batch

Before running any QoB job, make sure the configurations are set up correctly by doing:

# hailctl config set batch/billing_project all-by-aou
# hailctl config set batch/remote_tmpdir gs://aou_tmp
# hailctl config set batch/tmp_dir gs://aou_tmp
# hailctl config set query/backend batch
hailctl config list

Scripts

reformat_vat.py

  • Description:
    • Load the original .tsv.gz VAT from the original bucket
    • Parse the non-string fields to the correct datatype
    • Sort the table and key by locus and alleles
  • Usage: python3 reformat_vat.py

process_phenotype.py

  • Description:
    • Load original .csv phenotype files to HTs and parse the non-string fields to the correct datatype (--update-raw-phenotypes)
    • Load the .tsv sample information files to HTs and parse the non-string fields to the correct datatype (--update-sample-util-ht)
    • Merge the parsed phenotype HTs (--update-phenotype-ht) and annotate sample information (--annotate-phenotype-ht)
    • Generate sample meta information table with standard covariates to be used for association tests (--update-meta-ht)
  • Usage: python3 --update-sample-util-ht --update-raw-phenotypes --update-phenotype-ht --annotate-phenotype-ht --update-meta-ht
  • Options: --batch run jobs with Hail Batch in case nothing else works

pre_process_random_pheno.py

  • Description: pre-processing data to generate the GRM for producing population-specific random phenotypes
  • Usage: python3 pre_process_random_pheno.py --create-plink-file --create-sparse-grm --run-hail-ibd --ld-prune --pop all --overwrite
  • Options:
    • --pop can be a comma-separated list of any combinations from ['afr', 'amr', 'eas', 'eur', 'mid', 'sas', 'all']
    • --ld-prune whether to run ld pruning before exporting to plink files (required for GRM)

export_vds_to_bgen.py

  • Description: chunking VDS into Bgen files each covers an interval of approximately N_GENE_PER_GROUP genes
  • Usage: python3 export_vds_to_bgen.py --test --mean_impute_missing --update-vds