Dan Gustavson has computed polygenic scores (PGSs) using a standardized pipeline.

THIS PAGE IS STILL UNDER CONSTRUCTION. IF YOU HAVE QUESTIONS PLEASE EMAIL daniel.gustavson@colorado.edu

We started with the lightly QC'd genetic datafiles from Luke Evans that was imputed to HRC. Additional QC was then applied to remove INFO/R2⇐.80, remove multiallelic variants, and rename to RSID (build 37). Additional filters in plink were as follows: –geno .05 –maf .01 –mind .05 –hwe 1e-10

PGSs were then computed using PRScs (Ge et al., 2019) and/or SbayesR (Lloyd-Jones et al., 2019) software. See the table below for which specific traits have been scored. Example scripts for generating your own scores are provided on RC, but please contact Daniel Gustavson if you have any questions and/or want to request specific scores generated in the future.

The “CATSLife_Ancestry_1KGPCs_Jan2024.txt” file includes a few important pieces of information recommended for PGS analyses.

• Conversion from genetic IID to study ID needed to merge PGS output with phenotypic information
• Continental ancestry group. These were determined based on mapping CATSLife data to 1KG Phase 3. EUR, AFR, SAS, and EAS groups were classified if they were within 5 SDs of the population means based on the first 4 principal components. Because there is a lot more variability in the AMR (American) group, this based on 2 SDs on the first 4 principal components and required that they not already be classified in one of the other groups.
• 20 PCs are provided in this datafile. This PCA was run after combining CATSLife with 1KG Phase 3 so these values can be interpreted on the same scale as the 1KG Phase 3 participants.