## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) set.seed(1) ## ----setup-------------------------------------------------------------------- library(segtest) ## ----------------------------------------------------------------------------- drbounds(ploidy = 8) ## DR bounds gamfreq(g = 4, ploidy = 8, type = "polysomic") ## no DR gamfreq(g = 4, ploidy = 8, alpha = c(0.1, 0.01), type = "polysomic") ## Some DR ## ----------------------------------------------------------------------------- seg[seg$ploidy == 8 & seg$g == 4 & seg$mode %in% c("disomic", "both"), "p"] ## ----------------------------------------------------------------------------- n_pp_mix(g = 4, ploidy = 8) ## ----------------------------------------------------------------------------- gamfreq(g = 4, ploidy = 8, gamma = c(1, 0, 0), type = "mix") gamfreq(g = 4, ploidy = 8, gamma = c(0, 1, 0), type = "mix") gamfreq(g = 4, ploidy = 8, gamma = c(0, 0, 1), type = "mix") ## ----------------------------------------------------------------------------- gamfreq(g = 4, ploidy = 8, gamma = c(1, 1, 1)/3, type = "mix") ## ----------------------------------------------------------------------------- n_pp_mix(g = 1, ploidy = 8) gamfreq(g = 1, ploidy = 8, gamma = 1, type = "mix") n_pp_mix(g = 7, ploidy = 8) gamfreq(g = 7, ploidy = 8, gamma = 1, type = "mix") ## ----------------------------------------------------------------------------- beta_bounds(ploidy = 8) gamfreq(g = 1, ploidy = 8, gamma = 1, beta = 0.03, type = "mix") gamfreq(g = 7, ploidy = 8, gamma = 1, beta = 0.03, type = "mix") ## ----fig.alt="Bar plot of genotype frequencies."------------------------------ gf <- gf_freq( p1_g = 2, p1_ploidy = 6, p1_gamma = c(0.7, 0.3), p1_type = "mix", p2_g = 4, p2_ploidy = 6, p2_gamma = c(0.5, 0.5), p2_type = "mix") plot(gf, type = "h", xlab = "Genotype", ylab = "Frequency") ## ----------------------------------------------------------------------------- x <- c(rmultinom(n = 1, size = 10, prob = gf)) x ## ----------------------------------------------------------------------------- gl <- simgl(nvec = x) gl ## ----------------------------------------------------------------------------- ## With known genotypes sout1 <- seg_lrt(x = x, p1_ploidy = 6, p2_ploidy = 6, p1 = 2, p2 = 4) sout1$p_value ## With genotype likelihoods sout2 <- seg_lrt(x = gl, p1_ploidy = 6, p2_ploidy = 6, p1 = 2, p2 = 4) sout2$p_value ## ----------------------------------------------------------------------------- gl10 <- gl / log(10) seg_lrt(x = gl10, p1_ploidy = 6, p2_ploidy = 6, p1 = 2, p2 = 4)$p_value