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update app.R
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@jessyjli
jessyjli committed May 1, 2023
1 parent 8bdadca commit 8699777
Showing 1 changed file with 32 additions and 26 deletions.
58 changes: 32 additions & 26 deletions app.R
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Original file line number Diff line number Diff line change
Expand Up @@ -8,15 +8,16 @@ library(tidyr)
# Some initial setup:
# this will not work if underscores are in the orig.ident (only for some views)
# take in the file, get list of genes, get metadata numbers and categories, get pcs 1-9, and factors..
aggregate <- readRDS('Keller_more_clusterings.rds')
aggregate <- readRDS('~/Jessie/Research/Bioinfo/Gong_Q_UCD/mouse_fixed_scRNASeq_Feb_2023/Gong_aggregate_celltype_20230302.rds')
genes = aggregate@assays$RNA
reductions <- attributes(aggregate@reductions)
meta_nums <- colnames(dplyr::select_if(aggregate@meta.data, is.numeric))
meta_cats <- c(colnames(dplyr::select_if(aggregate@meta.data, is.character)), colnames(dplyr::select_if(aggregate@meta.data, is.factor)),colnames(dplyr::select_if(aggregate@meta.data, is.logical)))
meta_cats <- meta_cats[meta_cats != "orig.ident"]
mysplitbydefault <- "Health"
pcs <- list('PC_1','PC_2','PC_3','PC_4','PC_5','PC_6','PC_7','PC_8','PC_9')
use.pcs <- 1:50
mysplitbydefault <- "CellType"
#pcs <- list('PC_1','PC_2','PC_3','PC_4','PC_5','PC_6','PC_7','PC_8','PC_9')
pcs <- c('PC_1','PC_2','PC_3','PC_4','PC_5','PC_6','PC_7','PC_8','PC_9')
#use.pcs <- 1:50
#agg_cats <- colnames(dplyr::select_if(aggregate@meta.data, is.factor))
# TODO get reduction types as a list to choose from

Expand All @@ -25,23 +26,23 @@ server = function(input, output, session){

# update values based on input from ui
outVar_double = reactive({
if (input$dataset == 'Genes'){mydata=row.names(genes)}
if (input$dataset == 'Genes'){mydata=rownames(genes)}
else if (input$dataset == 'Numeric Metadata') {mydata=meta_nums}
else if (input$dataset == 'PCs') {mydata=pcs}
mydata
})

# update values based on input from ui
outVar_single = reactive({
if (input$dataset_single == 'Genes'){mydata=row.names(genes)}
if (input$dataset_single == 'Genes'){mydata=rownames(genes)}
else if (input$dataset_single == 'Numeric Metadata') {mydata=meta_nums}
else if (input$dataset_single == 'PCs') {mydata=pcs}
mydata
})

# update values based on input from ui
outVar_seperated = reactive({
if (input$dataset_seperated == 'Genes'){mydata=row.names(genes)}
if (input$dataset_seperated == 'Genes'){mydata=rownames(genes)}
else if (input$dataset_seperated == 'Numeric Metadata') {mydata=meta_nums}
else if (input$dataset_seperated == 'PCs') {mydata=pcs}
mydata
Expand Down Expand Up @@ -78,8 +79,8 @@ server = function(input, output, session){

# Numeric input list for the marker set (multiple =TRUE)
observe({
updateSelectInput(session, "numeric_b",
choices = row.names(genes)
updateSelectizeInput(session, "numeric_b",
choices = rownames(genes), server = TRUE
)})

# Only numeric input for the single marker plot
Expand All @@ -95,7 +96,6 @@ server = function(input, output, session){
)})



# Seperated Identity
observe({
updateSelectInput(session, "identity_seperated",
Expand Down Expand Up @@ -138,8 +138,8 @@ server = function(input, output, session){

# Multiple Feature Plot
observe({
updateSelectInput(session, "multiple_feature_list",
choices = row.names(genes)
updateSelectizeInput(session, "multiple_feature_list",
choices = rownames(genes), server = TRUE
)})

# Table Identity
Expand All @@ -163,7 +163,10 @@ server = function(input, output, session){
)})



# Documentation
output$markdown <- renderUI({
includeMarkdown("~/Jessie/Research/Bioinfo/Packages/scRNA_shiny-master/README.md")
})

# Marker Plot Double
output$MarkerGenePlot <- renderPlot({
Expand Down Expand Up @@ -217,7 +220,6 @@ server = function(input, output, session){
})



# Cluster Tree Plot
output$ClusterTree <- renderPlot({
Idents(aggregate) <- input$identity_tree
Expand Down Expand Up @@ -247,8 +249,6 @@ server = function(input, output, session){
order <- sort(levels(aggregate))
levels(aggregate) <- order
DimPlot(object = aggregate, group.by=input$multiple_feature_categorical_plot, pt.size=0.5, reduction = input$multiple_feature_reduction, label = T)


})


Expand Down Expand Up @@ -368,7 +368,7 @@ server = function(input, output, session){
output$MarkerSet <- renderPlot({
Idents(aggregate) <- input$categorical_b
markers = input$numeric_b
expr.cutoff = 3
expr.cutoff = 1
widedat <- FetchData(aggregate, markers)
widedat$Cluster <- Idents(aggregate)
longdat <- gather(widedat, key = "Gene", value = "Expression", -Cluster)
Expand All @@ -392,18 +392,22 @@ server = function(input, output, session){


ui <- fluidPage(

titlePanel("scRNA Seurat Analysis"),
sidebarLayout(
sidebarPanel(width = 12,
tabsetPanel(
tabPanel("Documentation", value=-999,
mainPanel(width = 12,
br(),
#includeMarkdown("docs/testing.md")
includeMarkdown("README.md")
)
tabPanel("Documentation", value=1,
uiOutput('markdown')
),


# tabPanel("Documentation", value=-999,
# mainPanel(width = 12,
# br(),
# uiOutput('markdown')
# includeMarkdown("markdown")
# )
# ),

tabPanel("Double Marker", value=2,
br(),
Expand Down Expand Up @@ -478,6 +482,8 @@ ui <- fluidPage(
br(),
selectInput("multiple_feature_categorical_plot", "Identity:",
c(meta_cats)),
selectInput("multiple_feature_reduction", "Reduction:",
c(reductions)),
selectizeInput("multiple_feature_list", "Primary Numeric: \n
- Csv format works best here if pasted in from premade lists. \n
- Optimal for >5 and <16 input. \n
Expand Down Expand Up @@ -534,7 +540,7 @@ ui <- fluidPage(
#h3(textOutput("caption")),
plotOutput("SeperatedFeature", height = "500px"),
plotOutput("SeperatedDim"),
plotOutput("SeperatedViolin", width="4000px"),
plotOutput("SeperatedViolin", width="2000px"),
tableOutput("SeperatedCounts")

)
Expand Down Expand Up @@ -578,7 +584,7 @@ ui <- fluidPage(
tableOutput("markers")
)
),
id = "tabselected"
# id = "tabselected"
)
),
mainPanel(width = 12)
Expand Down

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