R语言shiny~实现简单的GO富集分析

2020-05-24 14:48:53 浏览数 (1)

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

  • BP
  • CC
  • MF

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

代码语言:javascript复制
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="Pg00001nPg00002"),
                                      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)
代码语言:javascript复制
4312
8318
10874
55143
55388
991
6280
2305
9493
1062
3868
4605
9833
9133
6279
10403
8685
597
7153
23397
6278
79733
259266
1381
3627
27074
6241
55165
9787
7368
11065
55355
9582
220134
55872
51203
3669
83461
22974
10460
10563
4751
6373
8140
79019
820
10635
1844
4283
27299
结果

image.png

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