## ----包括= false ---------------------------------------------------------------------------------------------------------- knitr::opts_chunk$set( error = FALSE, warning=FALSE, message=FALSE, collapse = TRUE, comment = "#>" ) library("BiocStyle“） ＃＃ - - 设置 - - - - - - - - - - - - - - - - - - - - ---------------------------------------- library("snifter") library("scRNAseq") library("scran") library("scuttle") library("scater") library("ggplot2") theme_set(theme_bw()) set.seed(42) ## ----data--------------------------------------------------------------------- data <- ZeiselBrainData() data <- data[rowMeans(counts(data) != 0) > 0.05, ] data <- computeSumFactors(data, cluster = quickCluster(data)) data <- logNormCounts(data) data <- runPCA(data, ncomponents = 20) ## Convert this to a factor to use as colouring variable later data$level1class <- factor(data$level1class) ## ----run---------------------------------------------------------------------- mat <- reducedDim(data) fit <- fitsne(mat, random_state = 42L) ggplot() + aes(fit[, 1], fit[, 2], colour = data$level1class) + geom_point(pch = 19) + scale_colour_discrete(name = "Cell type") + labs(x = "t-SNE 1", y = "t-SNE 2") ## ----split-------------------------------------------------------------------- test_ind <- sample(nrow(mat), nrow(mat) / 2) train_ind <- setdiff(seq_len(nrow(mat)), test_ind) train_mat <- mat[train_ind, ] test_mat <- mat[test_ind, ] train_label <- data$level1class[train_ind] test_label <- data$level1class[test_ind] embedding <- fitsne(train_mat, random_state = 42L) ## ----plot-embed--------------------------------------------------------------- new_coords <- project(embedding, new = test_mat, old = train_mat) ggplot() + geom_point( aes(embedding[, 1], embedding[, 2], colour = train_label, shape = "Train" ) ) + geom_point( aes(new_coords[, 1], new_coords[, 2], colour = test_label, shape = "Test" ) ) + scale_colour_discrete(name = "Cell type") + scale_shape_discrete(name = NULL) + labs(x = "t-SNE 1", y = "t-SNE 2") ## ----------------------------------------------------------------------------- sessionInfo()