## ----style, echo=FALSE, results='asis', message=FALSE, dpi=400---------------- BiocStyle::markdown() knitr::opts_chunk$set(tidy = FALSE, message = FALSE) ## ----------------------------------------------------------------------------- library(MungeSumstats) ## ----eval=FALSE--------------------------------------------------------------- # #### Search for datasets #### # metagwas <- MungeSumstats::find_sumstats(traits = c("parkinson","alzheimer"), # min_sample_size = 1000) # head(metagwas,3) # ids <- (dplyr::arrange(metagwas, nsnp))$id ## ----echo=FALSE--------------------------------------------------------------- #### Search for datasets #### #error_dwnld <- # tryCatch( # metagwas <- MungeSumstats::find_sumstats(traits = c("parkinson", # "alzheimer"), # min_sample_size = 1000), # error = function(e) e, # warning = function(w) w # ) #if(exists("metagwas")&&is.data.frame(metagwas)){#if exists downloaded fine # head(metagwas,3) # ids <- (dplyr::arrange(metagwas, nsnp))$id #} #to speed up build just create results metagwas2 <- data.frame( id=c("ieu-a-298","ieu-b-2","ieu-a-297"), trait = rep("Alzheimer's disease",3), group_name = rep("public",3), year=c(2013, 2019, 2013), author=c("Lambert","Kunkle BW","Lambert"), consortium=c("IGAP", "Alzheimer Disease Genetics Consortium (ADGC), European Alzheimer's Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer's Disease Consortium (GERAD/PERADES),", "IGAP" ), sex=rep("Males and Females",3), population=rep("European",3), unit=c("log odds","NA","log odds"), nsnp=c(11633,10528610,7055882), sample_size=c(74046,63926,54162), build=rep("HG19/GRCh37",3), category=c("Disease","Binary","Disease"), subcategory=rep("Psychiatric / neurological",3), ontology=rep("NA",3), mr=rep(1,3), priority=c(1,0,2), pmid=c(24162737,30820047,24162737), sd=rep(NA,3), note=c("Exposure only; Effect allele frequencies are missing; forward(+) strand", "NA","Effect allele frequencies are missing; forward(+) strand"), ncase=c(25580,21982,17008), ncontrol=c(48466,41944,37154), N=c(74046,63926,54162) ) print(head(metagwas2,3)) ## ----eval=FALSE--------------------------------------------------------------- # datasets <- MungeSumstats::import_sumstats(ids = "ieu-a-298", # ref_genome = "GRCH37") ## ----echo=FALSE--------------------------------------------------------------- #don't actually run as this takes some time, use stashed version datasets <- list("ieu-a-298"=paste0(tempdir(),"/ieu-a-298.tsv.gz")) #stashed value datasets_data <- list("ieu-a-298"=system.file("extdata","ieu-a-298.tsv.gz", package="MungeSumstats")) ## ----------------------------------------------------------------------------- print(datasets) ## ----------------------------------------------------------------------------- results_df <- data.frame(id=names(datasets), path=unlist(datasets)) print(results_df) ## ---- eval=FALSE-------------------------------------------------------------- # datasets <- MungeSumstats::import_sumstats(ids = ids, # vcf_download = TRUE, # download_method = "axel", # nThread = max(2,future::availableCores()-2)) ## ----------------------------------------------------------------------------- utils::sessionInfo()