## ----包括= false ---------------------------------------------------------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(ggplot2) theme_set(theme_classic()) ## ----设置，消息= false ------------------------------------------------------------------------------------------------库（igraph）库（schex）库（tenxpbmcdata）库（scater）库（scran）库（ggrepel）## ----加载--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Tenx_pbmc3k <-tenxpbmcdata（dataset =“ pbmc3k”）ROWNAMES（TENX_PBMC3K）<-UniquifyFeatUreNames（Rowdata（rowdata（tenx_pbmc3k））-------------------------------------------------------------------------------------------------- rowdata（tenx_pbmc3k）$ mito <-grepl（“^mt-”，Rownames（tenx_pbmc3k））Coldata（tenx_pbmc3k）<-cbind（coldata（coldx_pbmc3k），percellqccmettics（tenx_pbcmcmetics（subset）= list（mt = rowdata（tenx_pbmc3k）$ mito））））rowdata（tenx_pbmc3k）<-cbind（rowdata（tenx_pbmc3k），perfeatureqccmetrics（tenx_pbmc3k）tenx_pbmc3k <-tenx_pbbc3k <-tenx_pbc3k3K3K <-tenx_pb，ata（tenx_pbmc3k）$ subsets_mt_percent> 50] libsize_drop <-isoutlier（tenx_pbmc3k $ total，nmads = 3，type = 3，type =“ log = true”，log = true）features_drop <--，log = true）tenx_pbmc3k <-tenx_pbmc3k [，！（libsize_drop |feature_drop）] ## ----滤清机------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ calculateaverage（tenx_pbmc3k）<0 tenx_pbmc3k <-tenx_pbmc3k [！rm_ind，] ## --------------------=FALSE, warning=FALSE--------------------------------------- tenx_pbmc3k <- scater:：lognormcounts（tenx_pbmc3k）## -------------------------------------------------------------------------------------------------------------------------------------- TenX_PBMC3K <-runpca（tenx_pbmc3k）set.seed（10）tenx_pbmc3k <-runumap（tenx_pbmc3k，dimred =“ pca”，dimred =“ pca”，spread = 1，min_dist = 0.4）--------------------------------------------------------------------------------------------------- snn_gr <- buildSNNGraph(tenx_pbmc3k, use.dimred = "PCA", k = 50) clusters <- cluster_louvain(snn_gr) tenx_pbmc3k$cluster <- factor(clusters$membership) ## ----calc-hexbin-------------------------------------------------------------- tenx_pbmc3k <- make_hexbin(tenx_pbmc3k, nbins = 40, dimension_reduction = "UMAP", use_dims=c(1,2)) ## ----plot-density, fig.height=7, fig.width=7---------------------------------- plot_hexbin_density(tenx_pbmc3k) ## ----plot-meta, fig.height=7, fig.width=7------------------------------------- plot_hexbin_meta(tenx_pbmc3k, col="cluster", action="majority") plot_hexbin_meta(tenx_pbmc3k, col="total", action="median") ## ----plot-meta-trad, fig.height=7, fig.width=7-------------------------------- plotUMAP(tenx_pbmc3k, colour_by="cluster") plotUMAP(tenx_pbmc3k, colour_by="total") ## ----plot-meta-label, message=FALSE, fig.height=7, fig.width=7---------------- label_df <- make_hexbin_label(tenx_pbmc3k, col="cluster") pp <- plot_hexbin_meta(tenx_pbmc3k, col="cluster", action="majority") pp + ggrepel::geom_label_repel(data = label_df, aes(x=x, y=y, label = label), colour="black", label.size = NA, fill = NA) ## ----plot-gene, fig.height=7, fig.width=7------------------------------------- gene_id <-"POMGNT1" plot_hexbin_feature(tenx_pbmc3k, type="logcounts", feature=gene_id, action="mean", xlab="UMAP1", ylab="UMAP2", title=paste0("Mean of ", gene_id)) ## ----plot-gene-trad, fig.height=7, fig.width=7-------------------------------- plotUMAP(tenx_pbmc3k, by_exprs_values="logcounts", colour_by=gene_id) ## ---- message=FALSE, fig.height=7, fig.width=7-------------------------------- plot_hexbin_feature_plus(tenx_pbmc3k, col="cluster", type="logcounts", feature="POMGNT1", action="mean") ## ----------------------------------------------------------------------------- gene_id <-"CD19" gg <- schex::plot_hexbin_feature(tenx_pbmc3k, type="logcounts", feature=gene_id, action="mean", xlab="UMAP1", ylab="UMAP2", title=paste0("Mean of ", gene_id)) gg + theme_void() ## ---- eval=FALSE-------------------------------------------------------------- # ggsave(gg, file="schex_plot.pdf")