## ----style-knitr, eval=TRUE, echo=FALSE, results="asis"----------------------------- BiocStyle::latex() ## ----include=FALSE------------------------------------------------------------------ library(knitr) opts_chunk$set( concordance = TRUE, background = "#f3f3ff" ) ## ----req---------------------------------------------------------------------------- library("LACE") data(longitudinal_sc_variants) names(longitudinal_sc_variants) ## ----req_se------------------------------------------------------------------------- library("SummarizedExperiment",attach.required=FALSE) T1 = t(longitudinal_sc_variants[[1]]) T2 = t(longitudinal_sc_variants[[2]]) T3 = t(longitudinal_sc_variants[[3]]) T4 = t(longitudinal_sc_variants[[4]]) concat_time_point = cbind(T1,T2,T3,T4) TimePointLabes = c(rep("T1", ncol(T1)), rep("T2", ncol(T2)), rep("T3", ncol(T3)), rep("T4", ncol(T4))) longitudinal_SE = SummarizedExperiment(assays = concat_time_point, colData = data.frame(TimePoint = TimePointLabes)) print(longitudinal_SE) ## ----example_weights---------------------------------------------------------------- lik_weights = c(0.2308772,0.2554386,0.2701754,0.2435088) ## ----example_error_rates------------------------------------------------------------ alpha = list() alpha[[1]] = c(0.02,0.01,0.01,0.01) alpha[[2]] = c(0.10,0.05,0.05,0.05) beta = list() beta[[1]] = c(0.10,0.05,0.05,0.05) beta[[2]] = c(0.10,0.05,0.05,0.05) head(alpha) head(beta) ## ----example_inference-------------------------------------------------------------- inference = LACE(D = longitudinal_sc_variants, lik_w = lik_weights, alpha = alpha, beta = beta, keep_equivalent = TRUE, num_rs = 5, num_iter = 10, n_try_bs = 5, num_processes = NA, seed = 12345, verbose = FALSE) ## ----example_inference_full--------------------------------------------------------- data(inference) print(names(inference)) ## ----example_plot------------------------------------------------------------------- clone_labels = c("ARPC2","PRAME","HNRNPC","COL1A2","RPL5","CCT8") longitudinal.tree = longitudinal.tree.plot(inference = inference, labels_show = "clones", clone_labels = clone_labels, legend_position = "topright") ## ----sessioninfo,results='asis',echo=FALSE------------------------------------------ toLatex(sessionInfo())