## ----include=FALSE------------------------------------------------------------ knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "FP-" ) ## ----setup, message=FALSE, warning=FALSE-------------------------------------- library(cophescan) ## ----message=FALSE, warning=FALSE--------------------------------------------- data("cophe_multi_trait_data") names(cophe_multi_trait_data) ## ----fig.width = 4, fig.height=4, fig.align = "center"------------------------ querytrait <- cophe_multi_trait_data$summ_stat[['Trait_1']] querysnpid <- cophe_multi_trait_data$querysnpid LD <- cophe_multi_trait_data$LD ## ----regManhat, fig.width = 4, fig.height=4, fig.align = "center"------------- # Additional field named 'position' is required for the Manahattan plot. It is a numeric vector of chromosal positions querytrait$position <- sapply(querytrait$snp, function(x) as.numeric(unlist(strsplit(x, "-"))[2])) plot_trait_manhat(querytrait, querysnpid) ## ----fig.width = 4, fig.height=4, fig.align = "center"------------------------ # Run cophescan under a single causal variant assumption by providing the snpid of the known causal variant for trait 1 = querysnpid res.single <- cophe.single(querytrait, querysnpid = querysnpid, querytrait='Trait_1') summary(res.single) ## ----------------------------------------------------------------------------- res.single.predict <- cophe.hyp.predict(res.single) (paste0('The predicted hypothesis is: ', res.single.predict$cophe.hyp.call, ' [PP.Hc =', round(res.single.predict$PP.Hc,3), ']' )) ## ----fig.width = 4, fig.height=4, fig.align = "center", message=FALSE--------- # Run cophescan with susie (multiple variants) by providing the snpid of the known causal variant for trait 1 = querysnpid querytrait$LD <- LD res.susie <- cophe.susie(querytrait, querysnpid = querysnpid, querytrait='Trait_1') summary(res.susie) res.susie.predict <- cophe.hyp.predict(res.susie) (paste0('The predicted hypothesis is: ', res.susie.predict$cophe.hyp.call, ' [PP.Hc =', round(res.susie.predict$PP.Hc,3), ']' ))