PRISM-models

Protein imputation models (cis + trans) for protein-wide association studies with GWAS summary statistics. One file per protein, holding the SNP weights, the per-SNP association table and the LD matrix.

path	cohort	models	version
UKB-EUR/CisTrans/<protein>.RData	UK Biobank Pharma Proteomics (Olink), European ancestry	2,877	2026-10-09
Fenland/CisTrans/<gene>_<SeqId>.RData	Fenland (SomaScan)	3,785	2026-09-18
deCODE/CisTrans/<deCODE file>.RData	deCODE (SomaScan)	4,708	2026-10-09

What this version fixes

UKB-EUR (2026-10-09)

• Effect allele corrected. For variants with MAF near 0.5, A1 named the other allele of BETA. The labels came from a batch-restricted frequency run, while the GWAS used the full sample. All trans loci were retrained, and the inflated R² values (some above 1) are gone.
• GRCh38 positions added to ss as POS.38.
• A trans locus that had silently failed to train (PPP1R12A locus 2) is now included.
• Trans loci are capped at 3 Mb, and positions use a repaired GRCh38 rsID map.

deCODE (2026-10-09)

• Strand flips corrected. deCODE alleles are on the GRCh38 strand and the LD panel is on GRCh37, so in reverse-oriented regions some SNPs got the wrong sign. Alleles are now complemented before alignment, and the affected trans loci were retrained.
• Trans loci are capped at 3 Mb.

Fenland (2026-09-18, first release)

• Indels are removed, and multi-gene assays use the union of all their genes' cis windows, across chromosomes. Trans loci are capped at 3 Mb.

How the models were built

Cis = target gene ± 1 Mb; trans = Bonferroni-significant SNPs outside cis (MHC removed), clumped and merged into loci. Each locus is trained on summary statistics as a SUMMIT ensemble (ElNet, LASSO, MCP, MNet, SCAD over six LD-clumping levels, PUMAS subsampling), with LD from 49,341 UK Biobank EUR individuals. The cis locus and all trans loci of a protein are then merged into one model.

• UKB-EUR: trans loci from our own GWAS on individual-level UKB-PPP data; cis from the BLISS UKB models.
• Fenland: trans and cis loci trained from the published Fenland summary statistics (N = 10,708).
• deCODE: trans loci from the published deCODE summary statistics; cis from the BLISS deCODE models.

File contents

object	content
weight	data.frame with one column, weight; rownames = SNP
ss	SNP CHR BP BETA SE P N A1 A2 MAF CIS LOCI R2 (UKB-EUR also has POS.38)
LD.ut, LD.snp	upper triangle of the LD matrix, and its SNP names
CHECKED, R2.PUMAS, stats, VALIDATION	training diagnostics

• A1 is the effect allele of BETA and weight.
• BP is GRCh37 for UKB-EUR and Fenland, and GRCh38 for deCODE.
• LOCI is 0 for cis and ≥ 1 for a trans locus.
• R2 is the locus's PUMAS R², so a model's total is sum(unique(ss$R2)).

Loading (R)

Only the upper triangle of the LD matrix is stored; load-model-slim.r rebuilds the full matrix.

source("load-model-slim.r")
m <- load_model_slim("UKB-EUR/CisTrans/A1BG.RData")   # m$weight, m$ss, m$matrix.LD

MANIFEST.md5 lists the md5 of every model file (md5sum -c MANIFEST.md5).