## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(GxEScanR) ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ covdatafile <- system.file("extdata", "covdata.rds", package = "GxEScanR") covdata <- readRDS(covdatafile) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(covdata[1:5,], caption = "First 5 Subjects") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ bdinfofile <- system.file("extdata", "pdata_4_1.bdinfo", package = "GxEScanR") bdinfo <- readRDS(bdinfofile) bdinfo$filename <- system.file("extdata", "pdata_4_1.bdose", package = "GxEScanR") ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ modeldf <- readRDS(system.file("extdata", "models.rds", package = "GxEScanR")) knitr::kable(modeldf, caption = "Models Fit") ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(modeldf[1,], caption = "Model Fit") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ lingwas1 <- gwas(data = covdata, bdinfo = bdinfo, binary = FALSE) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(lingwas1, caption = "Linear Regression GWAS") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ outfile <- tempfile() lingwas2 <- gwas(data = covdata, bdinfo = bdinfo, outfile = outfile, binary = FALSE) lingwas2 lingwas2 <- read.table(outfile, header = TRUE, sep ='\t') ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(lingwas2, caption = "Linear Regression GWAS") ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(modeldf[1:2,], caption = "Models Fit") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ lingweis1 <- gweis(data = covdata, bdinfo = bdinfo, minmaf = 0.2, binary = FALSE) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(lingweis1, caption = "Linear Regression GWEIS") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ skipfile = tempfile() lingweis2 <- gweis(data = covdata, bdinfo = bdinfo, skipfile = skipfile, minmaf = 0.2, binary = FALSE) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(lingweis2, caption = "Linear Regression GWEIS") skipsnps <- read.table(skipfile, header = TRUE, sep = '\t') ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ knitr::kable(skipsnps, caption = "Skipped SNPs") ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ reasondf <- readRDS(system.file("extdata", "skipreason.rds", package = "GxEScanR")) knitr::kable(reasondf, caption = "Skipped Reasons") ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(modeldf[1,], caption = "Model Fit") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ loggwas1 <- gwas(data = covdata, bdinfo = bdinfo, blksize = 2, binary = TRUE) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(loggwas1, caption = "Logistic Regression GWAS", digits = 4) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ defaultdf <- readRDS(system.file("extdata", "defaultblk.rds", package = "GxEScanR")) knitr::kable(defaultdf, caption = "Default blksize") ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(modeldf, caption = "Models Fit") ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ loggweis1 <- gweis(data = covdata, bdinfo = bdinfo, snps = 1:2, binary = TRUE) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(loggweis1, caption = "Logistic Regression GWEIS", digits = 4) ## ---- eval = T, echo = T, message = F, warning = F, tidy = T------------------ covdata2 <- covdata covdata2$e <- covdata2$e + 1 loggweis2 <- gweis(data = covdata2, bdinfo = bdinfo, snps = c("1:10001", "1:10002")) ## ---- eval = T, echo = F, message = F, warning = F, tidy = T------------------ knitr::kable(loggweis2, caption = "Logistic Regression GWEIS", digits = 4)