## ----install_package, eval=FALSE, collapse = TRUE----------------------------- # install.packages("CPBayes") # library("CPBayes") ## ----load_Beta, collapse = TRUE----------------------------------------------- library("CPBayes") # Load the beta hat vector BetaHatfile <- system.file("extdata", "BetaHat.rda", package = "CPBayes") load(BetaHatfile) BetaHat ## ----load_SE, collapse = TRUE------------------------------------------------- # Load the standard error vector SEfile <- system.file("extdata", "SE.rda", package = "CPBayes") load(SEfile) SE ## ----names, collapse = TRUE--------------------------------------------------- # Specify the name of the traits and the genetic variant. traitNames <- paste("Disease", 1:10, sep = "") SNP1 <- "rs1234" traitNames SNP1 ## ----example_analytic_calculation_uncor, collapse = TRUE---------------------- #Run analytic_locFDR_BF_uncor function to analytically compute locFDR and log10BF for uncorrelated summary statistics. result <- analytic_locFDR_BF_uncor(BetaHat, SE) str(result) ## ----uncor_example, collapse = TRUE------------------------------------------- # Run the uncorrelated version of CPBayes (based on MCMC). result <- cpbayes_uncor(BetaHat, SE, Phenotypes = traitNames, Variant = SNP1, MCMCiter = 5500, Burnin = 500) ## ----result_structure, collapse= TRUE----------------------------------------- # Overall summary of the primary results produced by cpbayes_uncor. str(result) ## ----post_summary, collapse= TRUE--------------------------------------------- # Post summary of the MCMC data produced by cpbayes_uncor. PleioSumm <- post_summaries(result, level = 0.05) str(PleioSumm) ## ----forest_plot, eval = FALSE, collapse= TRUE-------------------------------- # # Forest plot for the pleiotropy result obtained by cpbayes_uncor. # forest_cpbayes(result, level = 0.05) ## ----load_cBeta, collapse = TRUE---------------------------------------------- # Load the beta-hat vector datafile <- system.file("extdata", "cBetaHat.rda", package = "CPBayes") load(datafile) cBetaHat ## ----load_cSE, collapse = TRUE------------------------------------------------ # Load the standard error vector datafile <- system.file("extdata", "cSE.rda", package = "CPBayes") load(datafile) cSE ## ----load_cor, collapse = TRUE------------------------------------------------ # Load the correlation matrix of the beta-hat vector (cBetaHat) datafile <- system.file("extdata", "cor.rda", package = "CPBayes") load(datafile) cor ## ----example_analytic_calculation_cor, collapse = TRUE------------------------ # Run analytic_locFDR_BF_cor function to analytically compute locFDR and log10BF for correlated summary statistics. result <- analytic_locFDR_BF_cor(cBetaHat, cSE, cor) str(result) ## ----cor_example, collapse = TRUE--------------------------------------------- # Run the correlated version of CPBayes. result <- cpbayes_cor(cBetaHat, cSE, cor, Phenotypes = traitNames, Variant = SNP1, MCMCiter = 5500, Burnin = 500) ## ----result_structure_cor, collapse= TRUE------------------------------------- # Overall summary of the primary results produced by cpbayes_cor. str(result) ## ----post_summary_cor, collapse= TRUE----------------------------------------- # Post summary of the MCMC data produced by cpbayes_cor. PleioSumm <- post_summaries(result, level = 0.05) str(PleioSumm) ## ----forest_plot_cor, eval=FALSE, collapse= TRUE------------------------------ # # Forest plot for the pleiotropy result obtained by cpbayes_cor. # forest_cpbayes(result, level = 0.05) ## ----corln_estimation_example, collapse = TRUE-------------------------------- # Example data of sample-overlap matrices SampleOverlapMatrixFile <- system.file("extdata", "SampleOverlapMatrix.rda", package = "CPBayes") load(SampleOverlapMatrixFile) SampleOverlapMatrix ## ----run_corln_estimation, collapse = TRUE------------------------------------ # Estimate the correlation matrix of correlated beta-hat vector n11 <- SampleOverlapMatrix$n11 n00 <- SampleOverlapMatrix$n00 n10 <- SampleOverlapMatrix$n10 cor <- estimate_corln(n11, n00, n10) cor