library(shiny)
library(corrplot)
# Dataset
df <- data.frame(BM1 = c(30, 3, 34, 57, 100, 475),
BM2 = c(0.04, 0.9, 2, 4, 2.23, 3),
BM3 = c(2, 3, 4, 3, 10, 42),
BM4 = c(1, 1.1, 2, 4, 2, 3),
BM5 = c(3000, 30, 304, 507, 1000, 4075),
BM6 = c( 0.043, 20.9, 27, 84, 2.273, 63),
BM7 = c(304, 32, 34, 57, 100, 4753),
BM8 = c( 0.004, 10.9, 20, 4, 2.23, 31),
BM9 = c(301, 13, 314, 571, 10, 47),
BM10 = c( 0.24, 0.93, 12, 42, 23, 3000))
ui <- fluidPage(
titlePanel("Bring out correlation between several biomarkers"),
sidebarLayout(
sidebarPanel(
sliderInput(inputId = "slide0",
label = "Choose the number of variables",
min = 2,
max = 10,
value = c(1,10),
step = 1
)
),
mainPanel(
plotOutput(outputId = "pearson")
)
)
)
server <- function(input, output, session) {
output$pearson <- renderPlot({
corr <- cor(df[,1:input$slide0], method = "pearson", use = "pairwise.complete.obs")
corrplot(corr, type = "lower", method = "circle", tl.col = "black", tl.srt = 45)
})
}
这里是一个示例
答案 0 :(得分:3)
像这样吗?
library(shiny)
library(corrplot)
# Dataset
df <- data.frame(BM1 = c(30, 3, 34, 57, 100, 475),
BM2 = c(0.04, 0.9, 2, 4, 2.23, 3),
BM3 = c(2, 3, 4, 3, 10, 42),
BM4 = c(1, 1.1, 2, 4, 2, 3),
BM5 = c(3000, 30, 304, 507, 1000, 4075),
BM6 = c( 0.043, 20.9, 27, 84, 2.273, 63),
BM7 = c(304, 32, 34, 57, 100, 4753),
BM8 = c( 0.004, 10.9, 20, 4, 2.23, 31),
BM9 = c(301, 13, 314, 571, 10, 47),
BM10 = c( 0.24, 0.93, 12, 42, 23, 3000))
ui <- fluidPage(
titlePanel("Bring out correlation between several biomarkers"),
sidebarLayout(
sidebarPanel(
sliderInput(inputId = "slide0",
label = "Choose the number of variables",
min = 2,
max = 10,
value = c(1,10),
step = 1
)
),
mainPanel(
plotOutput(outputId = "pearson")
)
)
)
server <- function(input, output, session) {
output$pearson <- renderPlot({
corr <- cor(df[,input$slide0[1]:input$slide0[2]], method = "pearson", use = "pairwise.complete.obs")
corrplot(corr, type = "lower", method = "circle", tl.col = "black", tl.srt = 45)
})
}
shinyApp(ui=ui,server=server)