knitr::opts_chunk$set(dev="CairoPNG")
knitr::opts_chunk$set(echo = TRUE)
load("../data/reduced_map_qtl2_mapping_objects.Rdata") kinship <- qtl2::calc_kinship(probs = genoprobs.1, type = "loco") nc <- 64
library(magrittr) library(ggplot2)
dat <- readr::read_csv("../data/pheno_clinical_4qtl2_win2_05OCT2019_v4.csv") dmat <- as.matrix(dat[, -1]) rownames(dmat) <- dat$X1
sout <- qtl2::scan1(genoprobs = genoprobs.1, pheno = dmat, kinship = kinship, addcovar = addcovar) qtl2::find_peaks(sout, map.1, threshold = 6) %>% dplyr::arrange(chr) # KC peak: 20, lungCFU peak: 16
phe <- as.matrix(dat[, c("KC", "lungCFU")]) rownames(phe) <- dat$X1 start <- 1 end <- max(which(map.1$`7` < 30))
library(future.batchtools) library(future) plan("batchtools_multicore")
sp_out <- qtl2pleio::scan_pvl(probs = genoprobs.1$`7`, pheno = phe, addcovar = addcovar, kinship = kinship$`7`, start_snp = start, n_snp = end - start + 1) (lrt <- qtl2pleio::calc_lrt_tib(sp_out))
sp_out %>% qtl2pleio::calc_profile_lods() %>% qtl2pleio::add_pmap(pmap = map.1$`7`) %>% ggplot2::ggplot() + ggplot2::geom_line(ggplot2::aes(x = marker_position, y = profile_lod, colour = trait))
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