R语言shiny~实现简单的GO富集分析

用户7010445

发布于 2020-05-24 14:48:53

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代码可运行

文章被收录于专栏：小明的数据分析笔记本小明的数据分析笔记本

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代码可运行

模仿的是 https://github.com/sk-sahu/sig-bio-shiny

基本功能是用户输入

gene id
pvalue
qvalue

然后分别把

以表格输出，

汇总结果下载（压缩文件）
go富集结果的dotplot

代码

代码中 cc和mf结果表格输出的逻辑没有写，和bp是完全一样的

library(shiny)
ui<-navbarPage("Pomegranate",
               tabPanel("Gene Ontology",
                        sidebarLayout(sidebarPanel(width=2,
                                                   textAreaInput("text_area_list",
                                                                 label = "Please input protein id, one per line",
                                                                 height = "200px",
                                                                 width="180px",
                                                                 value="Pg00001\nPg00002"),
                                      selectInput("id_type",label = "Input gene-id Type",
                                                  selected = "ensembl",
                                                  choices = c('ensembl','refseq','entrezid')),
                                      helpText("Please"),
                                      numericInput('pval_cutoff',label="pvalue-Cutoff",
                                                   value = 1,min=0.001,max=1,step=0.001),
                                      numericInput("qval_cutoff",label="qvalue-Cutoff",
                                                   value=1,min=0.001,max=1,step=0.001),
                                      actionButton('submit',label = 'Submit',
                                                   icon=icon('angle-double-right')),
                                      tags$hr()),
                                      mainPanel(helpText("ABC"),
                                                downloadButton('download_plot',label = "Download results plot"),
                                                downloadButton('download_table',label="Download result table"),
                                                textOutput("gene_number_info"),
                                                tags$br(),
                                                tags$br(),
                                                tabsetPanel(
                                                  tabPanel("Biological Process",DT::dataTableOutput(outputId="table_go_bp")),
                                                  tabPanel("Cellular Component",DT::dataTableOutput(outputId = "table_go_cc")),
                                                  tabPanel("Molecular Functions",DT::dataTableOutput(outputId = 'table_go_mf')),
                                                  tabPanel("dotplot",plotOutput('dot_plot_go'))
                                                )))))
server<-function(input,output){
  observeEvent(input$submit,{
    withProgress(message = 'Steps:',value=0,{
      incProgress(1/7,detail = "A")
      text_area_input<-input$text_area_list
      print(text_area_input)
      df<-as.data.frame(matrix(unlist(stringr::str_split(text_area_input,"\n")),ncol=1))
      colnames(df)<-"protein_id"
      print(dim(df))
      input_gene_number<-dim(df)[1]
      output$gene_number_info<-renderText({
        paste("Done!","Total Number of Input genes:",input_gene_number,sep="\n")
      })
      incProgress(2/7,detail = "B")
      library(clusterProfiler)
      enrichGO_res<-enrichGO(gene=df$protein_id,
                             OrgDb = 'org.Hs.eg.db',
                             ont="all",
                             pvalueCutoff = input$pval_cutoff,
                             qvalueCutoff = input$qval_cutoff)
      go_enricher_res<-enrichGO_res@result
      go_bp<-go_enricher_res[go_enricher_res$ONTOLOGY == "BP",]
      output$table_go_bp<-DT::renderDataTable({
        go_bp
      })
      incProgress(3/7,detail="plot")
      output$dot_plot_go<-renderPlot({
        p1<-dotplot(enrichGO_res)
        print(p1)
      })
      incProgress(4/7,detail = "OK")
      go_plot_download<-reactive({
        dotplot(enrichGO_res)
      }
      )
      output$download_plot<-downloadHandler(
        filename = function(){
          paste("go_dot_plot.png",sep='')
        },
        content = function(file){
          ggplot2::ggsave(file,plot=go_plot_download(),device = 'png',width=12,height = 10)
        }
      )
      output$download_table<-downloadHandler(
        filename = function(){
          paste0("ABC.zip")
        },
        content = function(file){
          fs<-c('go_results.tsv')
          write.table(go_enricher_res,file="go_results.tsv",sep="\t",row.names = F)
          zip(zipfile = file,files=fs)
        },
        contentType = "application/zip"
      )
    })
  })
  }

shinyApp(ui,server)

界面是这样子的

image.png

用于做测试的 id (人)