## ----eval=FALSE--------------------------------------------------------------- # install.packages("BiocManager") # BiocManager::install("CAEN") ## ----message=FALSE,warning=FALSE---------------------------------------------- library(CAEN) library(SummarizedExperiment) ## ----------------------------------------------------------------------------- data("realData") realData ## ----message=FALSE, warning=FALSE--------------------------------------------- x <- realData y <- c(rep(1,18),rep(2,18)) xte <- realData prob <- estimatep(x = x, y = y, xte = x, beta = 1, type = "mle", prior = NULL) prob0 <- estimatep(x = x, y = y, xte = xte, beta = 1, type = "mle", prior = NULL) myscore <- CAEN(dataTable = x, y = y, K = 2, gene_no_list = 100) ## ----message=FALSE,warning=FALSE---------------------------------------------- ddd <- myscore$np datx <- t(assay(x)[ddd,]) datxte <- t(assay(xte)[ddd,]) probb <- prob[ddd,] probb0 <- prob0[ddd,] zipldacv.out <- ZIPLDA.cv(x = datx, y = y, prob0 = t(probb)) ZIPLDA.out <- ZIPLDA(x = datx, y = y, xte = datxte, transform = FALSE, prob0 = t(probb0),rho = zipldacv.out$bestrho) classResult <- ZIPLDA.out$ytehat ## ----------------------------------------------------------------------------- dat <- newCountDataSet(n = 100, p = 500, K = 4, param = 10, sdsignal = 2, drate = 0.2) ## ----message=FALSE, warning=FALSE--------------------------------------------- x <- t(assay(dat$sim_train_data)) y <- as.numeric(colnames(dat$sim_train_data)) xte <- t(assay(dat$sim_test_data)) prob <- estimatep(x = x, y = y, xte = x, beta = 1, type = c("mle","deseq","quantile"), prior = NULL) prob0 <- estimatep(x = x, y = y, xte = xte, beta = 1, type = c("mle","deseq","quantile"), prior = NULL) myscore <- CAEN(dataTable = assay(dat$sim_train_data), y = as.numeric(colnames(dat$sim_train_data)), K = 4, gene_no_list = 100) ## ----message=FALSE,warning=FALSE---------------------------------------------- ddd <- myscore$np datx <- x[,ddd] datxte <- xte[,ddd] probb <- prob[ddd,] probb0 <- prob0[ddd,] zipldacv.out <- ZIPLDA.cv(x = datx, y = y, prob0 = t(probb)) ZIPLDA.out <- ZIPLDA(x = datx, y = y, xte = datxte, transform = FALSE, prob0 = t(probb0), rho = zipldacv.out$bestrho) classResult <- ZIPLDA.out$ytehat ## ----------------------------------------------------------------------------- sessionInfo()