R/example/example_script.R

In amanda-tapia/LocusXcanR: What The Package Does (one line, title case required)

# directory
#dsdir <- "C:/Users/manda/OneDrive/Courses - UNC/Dissertation/Kaiser/RApp/"

# example header details
headernote <- "All genomic positions are from GRCh37.<p>TWAS results for 10 traits are presented in the figures and tables below. Traits and trait categories are listed and defined as follows:<p><ul><li>Platelet count (PLT)</li><li>Red blood cell indices (RBC): red blood cell count (RBC), hematocrit (HCT), hemoglobin (HGB), mean corpuscular volume (MCV), and red cell distribution width (RDW)</li><li>White blood cell indices (WBC): white blood cell count (WBC), monocyte (MONO), neutrophil (NEUTRO), and lymphocyte (LYMPH)</li></ul>"

# example methods
method <- source("R/example/methods.R")


# call the function
LocusXcanR(
         #twas_result = paste0(dsdir,"KaiserAnalysisDS.txt"),
         twas_result = "inst/extdata/twas_ds_single.txt",
         
         #known_variants = paste0(dsdir,"RBC_knownsnp.match.txt"),
         known_variants = "inst/extdata/gwas_sentinel.txt",
         
         #weight_tbl = paste0(dsdir,"DGN-weights.txt"),
         weight_tbl = "inst/extdata/weight_tbl.txt",
         
         #known_gwas = paste0(dsdir,"gwaspval_DGN.txt"),
         known_gwas = "inst/extdata/known_gwas.txt",
         
         #db_genes = paste0(dsdir,"DGN_genes_Kaiser.txt"),
         db_genes = "inst/extdata/db_genes.txt",

         #all_gwas = paste0(dsdir,"kaiser.gwas_locusALL.txt"),
         all_gwas = "inst/extdata/all_gwas.txt",
         
         #pred_exp_corr = paste0(dsdir,"DGN_expression_dec_cor.Rdata"),
         pred_exp_corr = "inst/extdata/pred_exp_corr.Rda",
         
         #ld_gwas = paste0(dsdir,"locusLD_topsub.ld"),
         ld_gwas = "inst/extdata/ld_gwas.txt",
         
         
         study_name = "Genetic Epidemiology Research on Adult Health and Aging (GERA) Europeans",
         ref_expr_name = "PredictDB Depression Genes and Networks (DGN) weights",
         head_details = headernote,
         method_details = method,
         conditional_present = TRUE,
         primary_tissue = "",
         meta_present = TRUE,
         multiple_tissues = FALSE,
         meta_thresh=2.09e-04,
         pvalthresh=6.35938,
         ideogram_present = TRUE,
         cytoband_ds = "inst/extdata/cytoBandIdeo.txt.gz",
         genome_build = "hg19")