## ----eval = FALSE------------------------------------------------------------- # install.packages("RapidoPGS") ## ----eval=FALSE--------------------------------------------------------------- # if (!requireNamespace("remotes", quietly = TRUE)) # install.packages("remotes") # remotes::install_github("GRealesM/RapidoPGS") ## ----message=FALSE, warning = FALSE------------------------------------------- library(RapidoPGS) ## ----eval =FALSE-------------------------------------------------------------- # ds <- gwascat.download(29059683) # # # Select the harmonised hg38 file # # This is equivalent to: # # ds <- fread("ftp://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST004001-GCST005000/GCST004988/harmonised/29059683-GCST004988-EFO_0000305.h.tsv.gz") # # # Then apply some reformatting # setnames(ds, old = c("hm_rsid","hm_chrom","hm_pos", "hm_other_allele", "hm_effect_allele", "hm_effect_allele_frequency", "hm_beta", "standard_error", "p_value"), new = c("SNPID","CHR", "BP", "REF","ALT","ALT_FREQ", "BETA", "SE", "P")) # ds <- ds[,.(SNPID, CHR, BP, REF, ALT, ALT_FREQ, BETA, SE, P)] # ds <- ds[CHR !="X"] # ds$CHR <- as.numeric(ds$CHR) # ds <- ds[order(CHR, BP)] # ds <- na.omit(ds, cols = c("BETA", "ALT_FREQ")) # ## ----------------------------------------------------------------------------- ds <- michailidou38 ## ----------------------------------------------------------------------------- summary(ds) ## ----------------------------------------------------------------------------- full_PGS <- rapidopgs_single(ds, trait = "cc", build = "hg38") ## ----------------------------------------------------------------------------- head(full_PGS) ## ----------------------------------------------------------------------------- PGS_1e4 <- rapidopgs_single(ds, trait ="cc", build = "hg38", filt_threshold = 1e-4) head(PGS_1e4) ## ----------------------------------------------------------------------------- PGS_1e4_norecalc <- rapidopgs_single(ds, trait ="cc", build = "hg38", filt_threshold = 1e-4, recalc = FALSE) head(PGS_1e4_norecalc) ## ----------------------------------------------------------------------------- PGS_top10 <- rapidopgs_single(ds, trait ="cc", build = "hg38", filt_threshold = 10) head(PGS_top10)