如何根据用户在 Shiny 中的输入显示不同的图？
How can I show different plots depending on the user's input in Shiny?
我有这个数据框：
> df
genes enst x y
1 Gene1 ENST1 25 14
2 Gene1 ENST2 60 25
3 Gene1 ENST3 12 5
4 Gene2 ENST1 9 34
5 Gene2 ENST2 14 12
6 Gene3 ENST1 10 1
我正在尝试创建一个 Shiny App，它允许我 select 基因和转录本。如果您 select 一个基因（例如 Gene1），您可以选择 select 您想要哪个转录本（在本例中为 ENST1、ENST2、ENST3）。
问题是我想画 2 个图。如果您单击“基因”（级别：基因），它将对该基因的所有值求和。
例如，对于具有 3 个转录本的第一个基因，x 的总值为 20+60+12=92，y 的总值为 14+25+5=44)。因此绘制基因 1 的值将是：x=92 和 y=44.
此外，我想绘制每个成绩单。例如，如果您 select“Gene1”和“Transcript 1”，绘图将使用 x=25 和 y=14。但是，如果用户决定选择两个转录本，则用户将看到 2 个图。或者，如果用户选择 3 个转录本，则用户将看到 3 个不同的图。
现在，使用我的代码：
如果您 select 基因，您将获得该基因的图。
但是，它会在同一图中显示所有成绩单。我只想显示一份成绩单（或更多，如果用户需要）
我不知道如何继续。
另一方面，有两件事我不知道如何实现。
- 一个动作按钮“看剧情”。 --- 如果你点击它，它会告诉你情节。
- 单选按钮“水平”---如果你点击基因，它只会显示基因图。但是，如果您单击成绩单，它会显示成绩单图。
有人能帮帮我吗？提前致谢
我的代码：
library(shiny)
################ DATA #############################
genes<- c("Gene1", "Gene1", "Gene1", "Gene2", "Gene2", "Gene3")
enst <- c("ENST1", "ENST2", "ENST3", "ENST1", "ENST2", "ENST1")
x <- c(25, 60, 12, 9, 14, 10)
y <- c(14, 25, 5, 34, 12, 1)
df<- data.frame(genes, enst, x, y)
###################################################
ui <- fluidPage(
# Application title
titlePanel("Barplot"),
sidebarLayout(
sidebarPanel(
uiOutput("selected_gene"),
uiOutput("selected_transcript"),
radioButtons("level", "Level:",
c("Gene" = "Gene",
"Transcript" = "Transcript")),
h5(strong("If you want to see the plot, you have to click the button")),
actionButton("add_plot", "See the plot"),
),
mainPanel(
plotOutput("plot"),
plotOutput("plot2"),
tableOutput("table1"),
tableOutput("table2")
)
)
)
server <- function(session, input, output) {
# This function gives us the list of genes.
genes_list <- reactive({
df$genes
})
transcripts_list <- reactive({
transcripts <- subset(df, df$genes==input$gene)
transcripts <- transcripts[,2]
return(transcripts)
})
# This function give us a select list input, in order to be able to select the gene that we want to see
output$selected_gene <- renderUI({
selectizeInput(inputId = "gene", "Select one gene", choices=genes_list(), options=list(maxOptions = length(genes_list())))
})
output$selected_transcript <- renderUI({
selectizeInput(inputId = "transcript", "Select one transcript", choices=transcripts_list(), options=list(maxOptions = length(transcripts_list())), multiple=T)
})
gene_values <- reactive({
values <- subset(df, df[1]==input$gene)
values$enst <- NULL
if(nrow(values)>1){ #for those genes who have more than 1 transcript
values_new <- values[2:length(values)]
values_new <- as.data.frame(t(colSums(values_new))) # sum the columns, transpose and transform into a dataframe
gene <- values[1,] #we take the first row, only one gene but all the info.
values <- cbind(values_new, gene[1]) # we bind both dataframes, however, we only want the gene name
values <- values[,c("genes",setdiff(names(values),"genes"))] # we move the last column at the beginning
}
return(values)
})
transc_values <- reactive({
values <- subset(df, df[1]==input$gene)
values$genes <- NULL
return(values)
})
plot_genes <- reactive({
gene_values <- gene_values()
barplot(c(gene_values$x, gene_values$y))
})
plot_transc <- reactive({
transc_values <- transc_values()
barplot(c(transc_values$x, transc_values$y))
})
v <- reactiveValues(plot = NULL)
observeEvent(input$add_plot, {
if(input$level == "Gene"){
v$plot <- plot_genes()
}
if(input$level == "Transcript"){
v$plot <- plot_transc()
}
})
# This function will draw the plot
# output$plot <- renderPlot({
# if (is.null(v$plot)){
# return()
# }
# v$plot
# })
output$table1 <- renderTable(gene_values())
output$table2 <- renderTable(transc_values())
output$plot <- renderPlot(plot_genes())
output$plot2 <- renderPlot(plot_transc())
}
shinyApp(ui, server)
或许你可以从这里入手，根据自己的需要进行修改。
library(shiny)
library(ggplot2)
library(DT)
################ DATA #############################
genes<- c("Gene1", "Gene1", "Gene1", "Gene2", "Gene2", "Gene3")
enst <- c("ENST1", "ENST2", "ENST3", "ENST1", "ENST2", "ENST1")
x <- c(25, 60, 12, 9, 14, 10)
y <- c(14, 25, 5, 34, 12, 1)
df<- data.frame(genes, enst, x, y)
###################################################
ui <- fluidPage(
# Application title
titlePanel("Histogram"),
sidebarLayout(
sidebarPanel(
uiOutput("selected_gene"),
uiOutput("selected_transcript"),
radioButtons("level", "Level:",
c("Gene" = "Gene",
"Transcript" = "Transcript")),
h5(strong("If you want to see the plot, you have to click the button")),
div(actionButton("add_plot", "See the plot"),
actionButton("table", "See the table"),
actionButton("clear", "Clear All")
)
),
mainPanel(
plotOutput("plot"),
DTOutput("table")
)
)
)
server <- function(input, output, session) {
## This function gives us the list of genes.
genes_list <- reactive({
unique(df$genes)
})
transcripts_list <- reactive({
req(input$gene)
transcripts <- subset(df, df$genes==input$gene)
transcripts <- transcripts[,2]
return(unique(transcripts))
})
# This function give us a select list input, in order to be able to select the gene that we want to see
output$selected_gene <- renderUI({
selectizeInput(inputId = "gene", "Select one gene", choices=genes_list(), options=list(maxOptions = length(genes_list())))
})
output$selected_transcript <- renderUI({
selectizeInput(inputId = "transcript", "Select one transcript", choices=transcripts_list(), options=list(maxOptions = length(transcripts_list())), multiple=F)
})
gene_values <- reactive({
req(input$gene)
values <- subset(df, df[1]==input$gene)
values$enst <- NULL
if(nrow(values)>1){ #for those genes who have more than 1 transcript
values_new <- values[2:length(values)]
values_new <- as.data.frame(t(colSums(values_new))) # sum the columns, transpose and transform into a dataframe
gene <- values[1,] #we take the first row, only one gene but all the info.
values <- cbind(values_new, gene[1]) # we bind both dataframes, however, we only want the gene name
values <- values[,c("genes",setdiff(names(values),"genes"))] # we move the last column at the beginning
}
return(values)
})
transc_values <- reactive({
req(input$transcript)
values <- subset(df, df[2]==input$transcript)
values$genes <- NULL
return(values)
})
mydata <- reactive({
req(input$level)
if(input$level == "Gene"){
df <- req(gene_values())
}else if(input$level == "Transcript"){
df <- req(transc_values())
}else df <- NULL
df
})
# plot_genes <- reactive({
# gene_values <- req(gene_values())
# barplot(c(gene_values$x, gene_values$y))
#
# })
#
# plot_transc <- reactive({
# transc_values <- req(transc_values())
# barplot(c(transc_values$x, transc_values$y))
#
# })
v <- reactiveValues(plot = NULL, table=NULL)
observeEvent(input$add_plot, {
v$plot <- ggplot(mydata(), aes(x=x,y=y)) + geom_bar(stat = "identity")
v$table <- NULL ### display only plot
},ignoreInit = TRUE)
observeEvent(input$table, {
v$table <- req(mydata())
v$plot <- NULL ### display only table
},ignoreInit = TRUE)
observeEvent(input$clear, {
v$table <- NULL
v$plot <- NULL
},ignoreInit = TRUE)
## This function will draw the plot
output$plot <- renderPlot({ v$plot })
output$table <- renderDT({ v$table })
}
shinyApp(ui, server)
我有这个数据框：
> df
genes enst x y
1 Gene1 ENST1 25 14
2 Gene1 ENST2 60 25
3 Gene1 ENST3 12 5
4 Gene2 ENST1 9 34
5 Gene2 ENST2 14 12
6 Gene3 ENST1 10 1
我正在尝试创建一个 Shiny App，它允许我 select 基因和转录本。如果您 select 一个基因（例如 Gene1），您可以选择 select 您想要哪个转录本（在本例中为 ENST1、ENST2、ENST3）。
问题是我想画 2 个图。如果您单击“基因”（级别：基因），它将对该基因的所有值求和。 例如，对于具有 3 个转录本的第一个基因，x 的总值为 20+60+12=92，y 的总值为 14+25+5=44)。因此绘制基因 1 的值将是：x=92 和 y=44.
此外，我想绘制每个成绩单。例如，如果您 select“Gene1”和“Transcript 1”，绘图将使用 x=25 和 y=14。但是，如果用户决定选择两个转录本，则用户将看到 2 个图。或者，如果用户选择 3 个转录本，则用户将看到 3 个不同的图。
现在，使用我的代码：
如果您 select 基因，您将获得该基因的图。
但是，它会在同一图中显示所有成绩单。我只想显示一份成绩单（或更多，如果用户需要）
我不知道如何继续。
另一方面，有两件事我不知道如何实现。
- 一个动作按钮“看剧情”。 --- 如果你点击它，它会告诉你情节。
- 单选按钮“水平”---如果你点击基因，它只会显示基因图。但是，如果您单击成绩单，它会显示成绩单图。
有人能帮帮我吗？提前致谢
我的代码：
library(shiny)
################ DATA #############################
genes<- c("Gene1", "Gene1", "Gene1", "Gene2", "Gene2", "Gene3")
enst <- c("ENST1", "ENST2", "ENST3", "ENST1", "ENST2", "ENST1")
x <- c(25, 60, 12, 9, 14, 10)
y <- c(14, 25, 5, 34, 12, 1)
df<- data.frame(genes, enst, x, y)
###################################################
ui <- fluidPage(
# Application title
titlePanel("Barplot"),
sidebarLayout(
sidebarPanel(
uiOutput("selected_gene"),
uiOutput("selected_transcript"),
radioButtons("level", "Level:",
c("Gene" = "Gene",
"Transcript" = "Transcript")),
h5(strong("If you want to see the plot, you have to click the button")),
actionButton("add_plot", "See the plot"),
),
mainPanel(
plotOutput("plot"),
plotOutput("plot2"),
tableOutput("table1"),
tableOutput("table2")
)
)
)
server <- function(session, input, output) {
# This function gives us the list of genes.
genes_list <- reactive({
df$genes
})
transcripts_list <- reactive({
transcripts <- subset(df, df$genes==input$gene)
transcripts <- transcripts[,2]
return(transcripts)
})
# This function give us a select list input, in order to be able to select the gene that we want to see
output$selected_gene <- renderUI({
selectizeInput(inputId = "gene", "Select one gene", choices=genes_list(), options=list(maxOptions = length(genes_list())))
})
output$selected_transcript <- renderUI({
selectizeInput(inputId = "transcript", "Select one transcript", choices=transcripts_list(), options=list(maxOptions = length(transcripts_list())), multiple=T)
})
gene_values <- reactive({
values <- subset(df, df[1]==input$gene)
values$enst <- NULL
if(nrow(values)>1){ #for those genes who have more than 1 transcript
values_new <- values[2:length(values)]
values_new <- as.data.frame(t(colSums(values_new))) # sum the columns, transpose and transform into a dataframe
gene <- values[1,] #we take the first row, only one gene but all the info.
values <- cbind(values_new, gene[1]) # we bind both dataframes, however, we only want the gene name
values <- values[,c("genes",setdiff(names(values),"genes"))] # we move the last column at the beginning
}
return(values)
})
transc_values <- reactive({
values <- subset(df, df[1]==input$gene)
values$genes <- NULL
return(values)
})
plot_genes <- reactive({
gene_values <- gene_values()
barplot(c(gene_values$x, gene_values$y))
})
plot_transc <- reactive({
transc_values <- transc_values()
barplot(c(transc_values$x, transc_values$y))
})
v <- reactiveValues(plot = NULL)
observeEvent(input$add_plot, {
if(input$level == "Gene"){
v$plot <- plot_genes()
}
if(input$level == "Transcript"){
v$plot <- plot_transc()
}
})
# This function will draw the plot
# output$plot <- renderPlot({
# if (is.null(v$plot)){
# return()
# }
# v$plot
# })
output$table1 <- renderTable(gene_values())
output$table2 <- renderTable(transc_values())
output$plot <- renderPlot(plot_genes())
output$plot2 <- renderPlot(plot_transc())
}
shinyApp(ui, server)
或许你可以从这里入手，根据自己的需要进行修改。
library(shiny)
library(ggplot2)
library(DT)
################ DATA #############################
genes<- c("Gene1", "Gene1", "Gene1", "Gene2", "Gene2", "Gene3")
enst <- c("ENST1", "ENST2", "ENST3", "ENST1", "ENST2", "ENST1")
x <- c(25, 60, 12, 9, 14, 10)
y <- c(14, 25, 5, 34, 12, 1)
df<- data.frame(genes, enst, x, y)
###################################################
ui <- fluidPage(
# Application title
titlePanel("Histogram"),
sidebarLayout(
sidebarPanel(
uiOutput("selected_gene"),
uiOutput("selected_transcript"),
radioButtons("level", "Level:",
c("Gene" = "Gene",
"Transcript" = "Transcript")),
h5(strong("If you want to see the plot, you have to click the button")),
div(actionButton("add_plot", "See the plot"),
actionButton("table", "See the table"),
actionButton("clear", "Clear All")
)
),
mainPanel(
plotOutput("plot"),
DTOutput("table")
)
)
)
server <- function(input, output, session) {
## This function gives us the list of genes.
genes_list <- reactive({
unique(df$genes)
})
transcripts_list <- reactive({
req(input$gene)
transcripts <- subset(df, df$genes==input$gene)
transcripts <- transcripts[,2]
return(unique(transcripts))
})
# This function give us a select list input, in order to be able to select the gene that we want to see
output$selected_gene <- renderUI({
selectizeInput(inputId = "gene", "Select one gene", choices=genes_list(), options=list(maxOptions = length(genes_list())))
})
output$selected_transcript <- renderUI({
selectizeInput(inputId = "transcript", "Select one transcript", choices=transcripts_list(), options=list(maxOptions = length(transcripts_list())), multiple=F)
})
gene_values <- reactive({
req(input$gene)
values <- subset(df, df[1]==input$gene)
values$enst <- NULL
if(nrow(values)>1){ #for those genes who have more than 1 transcript
values_new <- values[2:length(values)]
values_new <- as.data.frame(t(colSums(values_new))) # sum the columns, transpose and transform into a dataframe
gene <- values[1,] #we take the first row, only one gene but all the info.
values <- cbind(values_new, gene[1]) # we bind both dataframes, however, we only want the gene name
values <- values[,c("genes",setdiff(names(values),"genes"))] # we move the last column at the beginning
}
return(values)
})
transc_values <- reactive({
req(input$transcript)
values <- subset(df, df[2]==input$transcript)
values$genes <- NULL
return(values)
})
mydata <- reactive({
req(input$level)
if(input$level == "Gene"){
df <- req(gene_values())
}else if(input$level == "Transcript"){
df <- req(transc_values())
}else df <- NULL
df
})
# plot_genes <- reactive({
# gene_values <- req(gene_values())
# barplot(c(gene_values$x, gene_values$y))
#
# })
#
# plot_transc <- reactive({
# transc_values <- req(transc_values())
# barplot(c(transc_values$x, transc_values$y))
#
# })
v <- reactiveValues(plot = NULL, table=NULL)
observeEvent(input$add_plot, {
v$plot <- ggplot(mydata(), aes(x=x,y=y)) + geom_bar(stat = "identity")
v$table <- NULL ### display only plot
},ignoreInit = TRUE)
observeEvent(input$table, {
v$table <- req(mydata())
v$plot <- NULL ### display only table
},ignoreInit = TRUE)
observeEvent(input$clear, {
v$table <- NULL
v$plot <- NULL
},ignoreInit = TRUE)
## This function will draw the plot
output$plot <- renderPlot({ v$plot })
output$table <- renderDT({ v$table })
}
shinyApp(ui, server)