## ----import_libraries, message=FALSE, warning=FALSE--------------------------- library("Nebulosa") library(“ scater”）库（“ scran”）库（“ dropletutils”）库（“ biocfilecache”）## --------------------------------------------------------------------------------------------------------------------------------------------------------------------- bfc <- BiocFileCache(ask = FALSE) data_file <- bfcrpath(bfc, file.path( "https://s3-us-west-2.amazonaws.com/10x.files/samples/cell“，” pbmc3k“，” pbmc3k_filtered_gene_gene_bc_matrices.tar.tar.tar.gz'- read10xcounts（file.path（tempdir（），“ filtered_gene_bc_matrices”，“ hg19”））## ---------------------------------------------------------------------------------------------------------------------------------------------------------- rownames(pbmc) <- uniquifyFeatureNames(rowData(pbmc）[[“ id”]，Rowdata（PBMC）[[“符号”]）## --------------------------------------------------------------------------------------------------------------------------------------------------- i <-Rowsums（counts（pbmc）> 0）is_expressed <- i> 3 pbmc <-pbmc [is_expressed，] ## ----滤波器---------------------------------------------------------------------------------------------------------------------------------------------------------- i <-Colsums（couts（pbmc）> 0）is_expressed <-i> 200 pbmc <-pbmc [，is_expressed] ## -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------，----------------------------------------------------------- iS_MITO <-grepl（“^mt-”，ROWNAMES（PBMC））QCSTATS <-percellqcmetrics（pbmc，subsets = list（mito = is_mito））qcfilter <-quickpercellqc（qcstats，percen_subsets = c（“ subsets_mito_percent”）------------------------------------------------------------------------------------------------- logcounts（pbmc）<-log1p（counts（pbmc） / colsums（counts（pbmc）） * 1E4）## ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ dec <-Modelgenevar（pbmc）top_hvgs <-getTophvgs（dec，n = 3000）## ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- set.seed(66)pBMC <-runpca（pbmc，scale = true，subset_row = top_hvgs）## ---------------------------------------------------------------------------------------------------------------------------------------- pbmc <- runUMAP(pbmc, dimred =“ PCA”）## ----聚类--------------------------------------------------------------------------------------------------------------------------------------------------------------- g <-buldsnngraph(pbmc, k = 10, use.dimred = "PCA") clust <- igraph::cluster_louvain(g)$membership colLabels(pbmc) <- factor(clust) ## ----plot_cd4----------------------------------------------------------------- plot_density(pbmc, "CD4") ## ----cd4_comparison----------------------------------------------------------- plotUMAP(pbmc, colour_by = "CD4") ## ----fig.height=10------------------------------------------------------------ p3 <- plot_density(pbmc, c("CD8A", "CCR7")) p3 + plot_layout(ncol = 1) ## ----fig.height=14------------------------------------------------------------ p4 <- plot_density(pbmc, c("CD8A", "CCR7"), joint = TRUE) p4 + plot_layout(ncol = 1) ## ----clusters----------------------------------------------------------------- plotUMAP(pbmc, colour_by = "label", text_by = "label") ## ----combine_param------------------------------------------------------------ p_list <- plot_density(pbmc, c("CD8A", "CCR7"), joint = TRUE, combine = FALSE) p_list[[length(p_list)]] ## ----joint, fig.height=14----------------------------------------------------- p4 <- plot_density(pbmc, c("CD4", "CCR7"), joint = TRUE) p4 + plot_layout(ncol = 1)