Skip to contents

Create a polygenic score

Source: R/create_pgs.R
create_pgs.Rd

Use user-provided list of genetic variants with weights for a trait to create a polygenic score. Uses the imputed BGEN files (field 22828) or WGS DRAGEN BGEN files (field 24309) data and load as data.frame

If selecting the DRAGEN data as the source, this assumes your project has access to the WGS BGEN files released April 2025. If not, run `ukbrapR:::make_dragen_bed_from_pvcfs()` to use [tabix] and [plink] to subset the [DRAGEN WGS pVCF files].

Usage

create_pgs(
  in_file,
  out_file = "tmp",
  pgs_name = "pgs",
  source = "imputed",
  use_imp_pos = FALSE,
  is_bed = FALSE,
  overwrite = FALSE,
  progress = FALSE,
  verbose = FALSE,
  very_verbose = FALSE
)

Arguments

in_file

A data frame or file path. Must contain rsid, chr, pos, effect_allele, other_allele, beta. For imputed genos pos is build 37. For DRAGEN pos is build 38. Other columns are ignored.

out_file

A string. Prefix for output files (optional) default="tmp"

pgs_name

A string. Variable name for created PGS (optional) default="pgs"

source

A string. Either "imputed" or "dragen" - indicating whether the variants should be from "UKB imputation from genotype" (field 22828) or "DRAGEN population level WGS variants, PLINK format [500k release]" (field 24308). Can instead be a path to a local BED file, if `is_bed=TRUE`. default="imputed"

use_imp_pos

Logical. If source imputed, use position instead of rsID to extract variants?, default=FALSE

is_bed

Logical. If you already have a BED file containing the required variants set this to TRUE and provide a path to the BED file in the `source` option, default=FALSE

overwrite

Logical. Overwrite output BED files? (If out_file is left as 'tmp' overwrite is set to TRUE), default=FALSE

progress

Logical. Show progress through each individual file, default=FALSE

verbose

Logical. Be verbose (show individual steps), default=FALSE

very_verbose

Logical. Be very verbose (show individual steps & show terminal output from Plink etc), default=FALSE

Value

A data frame

Author

Luke Pilling

Examples


# example variant list and weights from GWAS of liver cirrhosis 
#  - Innes 2020 Gastroenterology doi:10.1053/j.gastro.2020.06.014
#  - Position in build 38
varlist <- system.file("files", "pgs_liver_cirrhosis.txt", package="ukbrapR")

# Create PGS from imputed data using RSID
liver_pgs <- create_pgs(in_file=varlist, out_file="liver_cirrhosis.imputed.pgs", pgs_name="liver_cirrhosis_imputed_pgs")

# Create PGS from DRAGEN WGS data using CHR and POS
liver_pgs <- create_pgs(in_file=varlist, out_file="liver_cirrhosis.dragen.pgs", pgs_name="liver_cirrhosis_dragen_pgs", source="dragen")

# For these allele weights, we has position in build 37 and will get imputed data using this not RSIDs
#  - Bladder Cancer GWAS, Graff 2021 (https://doi.org/10.1038/s41467-021-21288-z)
varlist2 <- readr::read_tsv("https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000071/ScoringFiles/Harmonized/PGS000071_hmPOS_GRCh37.txt.gz", comment="#")
varlist2 <- varlist2 |> dplyr::rename(chr=chr_name, pos=chr_position)
bladder_cancer_pgs  <- create_pgs(in_file=varlist2, out_file="bladder_cancer.imputed.pgs", pgs_name="bladder_cancer_imputed_pgs", use_imp_pos=TRUE)