## ----包括= false ---------------------------------------------------------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup, eval=FALSE------------------------------------------------------------------------------------------ ＃library（shiny）＃library（seurat）＃library（ggrepel）＃library（shinydashboard）＃library（schex）＃library（isee）## -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ＃pbmc_small <-sake_hexbin（pbmc_small，nbins = 10，dimension_reduction =“ pca”）＃df_label <-make_hexbin_label（pbmc_small（pbmc_small）-----------------------------------------------------------------------------------------＃app <-shinyapp（＃server = function（input，output）{＃＃输出$ all_genes <-Renderui（{＃selectInput（inputId =“ gene”，label =“ gene”，＃选择= rownames = rownames = rownames（pbmc_small））＃}）＃＃＃输出$ plot1 < - renderplot（{＃plot_hexbin_meta（pbmc_small，“ rna_snn_res.0.8”，action =“多数派”，＃ggrepel :: geom_label_repel（data = df_label，＃aes（x = x，y = y，label = label），color =“ black”，＃label.size = na，fill = na）＃＃}）＃＃＃upput $ plot2 <-Renderplot（{＃plot_hexbin_feature（pbmc_small，type = input $ type，feature = input $ gene，＃action = input $ action，title = input $ gene）＃}）＃＃}，＃ui = dashboardpage（skin =“ purple”，＃dashboardheader（＃dashboardheader）），＃dashboardsidebar（＃uioutput（“ all_genes”），＃radiobuttons（“ type”，“”类型表达式：“，＃c（“ raw” =“ counts”，＃“ counts”，＃“ normalized” =“ data”），＃），＃radiobuttons（“ action”，“总结使用：”，＃c（“比例不是0” =“ prop_0”，＃“ mean” =“ mean”，nece'，＃“中间” =“中间”）＃＃），＃dashboardbody（＃fluidrow（＃box（plotOutput（“ plot1”，width = 450，高度= 400），宽度= 6），＃box（plotOutput（“ plot2”，width = 500，高度= 400），宽度= 6））））））） # ) # ) # ) ## ----convert, eval=FALSE------------------------------------------------------ # pbmc_small <- as.SingleCellExperiment(pbmc_small) # pbmc_small <- make_hexbin(pbmc_small, nbins=10, dimension_reduction = "PCA") ## ---- eval=FALSE-------------------------------------------------------------- # plot_hexbin_gene_new <- function(sce, rows=NULL, rownames=character(0), # columns=NULL, type="logcounts", action="prop_0"){ # # plot_hexbin_feature(sce, type=type, feature=rownames, action=action) # } ## ---- eval=FALSE-------------------------------------------------------------- # schex_plot_gene <- customDataPlotDefaults(pbmc_small, 1) # schex_plot_gene$Function <- "plot_hexbin_gene_new" # schex_plot_gene$Arguments <- "type counts\naction prop_0\nrownames ODC1" # schex_plot_gene$ColumnSource <- "NULL" # schex_plot_gene$RowSource <- "NULL" # schex_plot_gene$DataBoxOpen <- TRUE # # # app <- iSEE( # pbmc_small, # customDataArgs=schex_plot_gene, # initialPanels=DataFrame( # Name=c("Custom data plot 1"), # Width=c(12)), # customDataFun=list(plot_hexbin_gene_new=plot_hexbin_gene_new) # )