## ----eval=FALSE--------------------------------------------------------------- # install.packages("BiocManager") # BiocManager::install("MEB") ## ----------------------------------------------------------------------------- library(MEB) ## ----------------------------------------------------------------------------- data(sim_data_sp) sim_data_sp ## ----------------------------------------------------------------------------- data(real_data_sp) real_data_sp ## ----------------------------------------------------------------------------- data(sim_data_dsp) sim_data_dsp ## ----------------------------------------------------------------------------- data(real_data_dsp) real_data_dsp ## ----message = FALSE, warning = FALSE----------------------------------------- library(SummarizedExperiment) ## ----------------------------------------------------------------------------- data(sim_data_sp) gamma <- seq(1e-06,5e-05,1e-06) sim_model_sp <- NIMEB(countsTable=assay(sim_data_sp), train_id=1:1000, gamma, nu = 0.01, reject_rate = 0.05, ds = FALSE) ## ----------------------------------------------------------------------------- data(real_data_sp) gamma <- seq(1e-06,5e-05,1e-06) real_model_sp <- NIMEB(countsTable=assay(real_data_sp), train_id=1:530, gamma, nu = 0.01, reject_rate = 0.1, ds = FALSE) ## ----------------------------------------------------------------------------- data(sim_data_dsp) gamma <- seq(1e-07,2e-05,1e-06) sim_model_dsp <- NIMEB(countsTable=assay(sim_data_dsp), train_id=1:1000, gamma, nu = 0.01, reject_rate = 0.1, ds = TRUE) ## ----------------------------------------------------------------------------- data(real_data_dsp) gamma <- seq(5e-08,5e-07,1e-08) real_model_dsp <- NIMEB(countsTable=assay(real_data_dsp), train_id=1:143, gamma, nu = 0.01, reject_rate = 0.1, ds = TRUE) ## ----------------------------------------------------------------------------- sim_model_sp_pred <- predict(sim_model_sp$model, assay(sim_data_sp)) summary(sim_model_sp_pred) ## ----message = FALSE, warning = FALSE----------------------------------------- library(SingleCellExperiment) ## ----------------------------------------------------------------------------- data(sim_scRNA_data) sim_scRNA_data ## ----------------------------------------------------------------------------- data(stable_gene) head(stable_gene) length(stable_gene) ## ----------------------------------------------------------------------------- sim_scRNA <- scMEB(sce=sim_scRNA_data, stable_idx=stable_gene, filtered = TRUE, gamma = seq(1e-04,0.001,1e-05), nu = 0.01, reject_rate = 0.1) ## ----------------------------------------------------------------------------- sim_scRNA_pred <- predict(sim_scRNA$model, sim_scRNA$dat_pca) summary(sim_scRNA_pred) ## ----------------------------------------------------------------------------- table(sim_scRNA$dist>0) ## ----------------------------------------------------------------------------- sim_scRNA_dist <- data.frame(Gene=rownames(sim_scRNA_data), Distance=sim_scRNA$dist) head(sim_scRNA_dist) ## ----------------------------------------------------------------------------- sessionInfo()