GBE Global Meta-Analysis

[yk-tanigawa]

GBE Global Meta-Analysis

Summary

While we have UKB M-A in #22, we will also perform a meta-analysis across cohorts.

This involves several tasks.

1. Prepare summary statistics.

• Format conversion to plink2 format because most of the analysis pipeline were designed for that format
• Apply liftOver so that we have the summary statistics in hg19 coordinate.
• We should also make sure that the same variants have the same IDs because Metal uses the variant ID column in the input file.
• We will also prepare summary statistics in LDSC munge format (see the LDSC rg section below).

2. Identify the phenotyping mapping across cohorts

• We don't have GBE_ID for other cohorts. We will generate the phenotype mapping to enable M-A.
• To perform a semi-automated mapping assignment, we will apply LDSC rg.

3. Perform the meta-analysis

• We apply Metal as in UKB Meta-analysis #22

[yk-tanigawa]

• FinnGen R3 summary statistics was prepared.
  • We applied liftOver and prepared the files in LDSC munge format.
• UK Biobank we are preparing the UKB sumstats in LDSC munge format.
  • Need coordination with GWAS finishing effort - Simple line counts check #21. We prioritize the conversion for the finalized summary statistics for now.
• BBJ
  • We have processed files before
• MVP
  • We have processed files before