R/app.R
In kdgosik/scRipt: Single Cell R Interactive Playground Tool
Defines functions
server
#' ShinyUI
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' @param id The namespace for the shiny application.
#' @return shinyUI for module
#' @export
#' @import shiny
#' @import shinyFiles
#' @import cellranger
#' @author Kirk Gosik <kgosik@broadinstitute.org>
#' @examples
# if cellranger R kit is not installed then install it
if( !{"cellrangerRkit" %in% installed.packages()} ) {
source("http://cf.10xgenomics.com/supp/cell-exp/rkit-install-2.0.0.R")
}
require(cellrangerRkit)
## comment out the source statements
## comment out the shinyApp() statement at bottom
## change line 110 to take away the ../
# source("ModularUMItSNEPlot.R") ## will move to main part of the package
# source("ModularClusterExplore10x.R") ## will move to main part of the package
# source("ModularIdentifytSNE.R") ## will move to main part of the package
ui <- shinyUI(
fluidPage(
# Application title
titlePanel("Gene Expression Explore"),
# Sidebar with a selector for genes
sidebarLayout(
sidebarPanel(
shiny::radioButtons(inputId = "task",
label = "Select Task",
choices = c("Create Output", "Select Data")),
conditionalPanel(
condition = "input.task == 'Create Output'",
shinyFiles::shinyDirButton(id = "file_path",
label = "10X Path",
title = "Button"),
shiny::p("eg ../filtered_gene_bc_matrices/hg19"),
shiny::textInput("project", "Project Title"),
shiny::textInput("tissue_type", "Tissue Type"),
shiny::textInput("cell_type", "Cell Type (if known)"),
shiny::sliderInput(inputId = "cells",
label = "Minimum Cells Per Gene",
value = 3,
min = 1,
max = 20),
shiny::sliderInput(inputId = "genes",
label = "Minimum Genes Per Cell",
value = 200,
min = 10,
max = 500),
shiny::sliderInput(inputId = "max_mt",
label = "Max Percent Mitochondrial Genes Present",
value = 0.05,
min = 0,
max = 0.5,
step = 0.01),
shiny::actionButton("create_output", "Create Output")
), # conditionalPanel
conditionalPanel(
condition = "input.task == 'Select Data'",
shinyFiles::shinyDirButton(id = "data_source",
label = "Created Output Path",
title = "Button"),
shiny::selectInput(inputId = "rds_file",
label = "Select RDS file",
choices = ""),
shiny::actionButton("read_data", "Read Data"),
shiny::uiOutput("ui_data_load")
) # conditionalPanel
), # sidebarPanel
mainPanel(
tabsetPanel(
tabPanel(title = "Introduction",
includeMarkdown("inst/www/AppIntroduction.md")
), # tabPanel
# Show the t-SNE plot
tabPanel(title = "Cellranger tSNE",
UMItSNEPlotUI("tSNE")
), # tabPanel
tabPanel(title = "Cellranger Cluster",
ClusterExplore10xUI("cluster_explore")
), # tabPanel
tabPanel(title = "Seurat",
textOutput("seurat"),
IdentifytSNEUI("seurat_out")
) # tabPanel
#), # tabPanel
#
# tabPanel(title = "Morpheus",
# MorpheusUI("morpheus_out")
#
# ) # tabPanel
) # tabsetPanel
) # mainPanel
) # sidebarLayout
) # fluidPage
) # shinyUI
#' ShinyServer
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' @param id shiny id
#' @return shinyUI for module
#' @export
#' @param input List-like object that stores the current values of all of the widgets in your app.
#' @param output List-like object that stores instructions for building the R objects in your app.
#' @param session List-like object about the session to be passed to the UI.
#' @import shiny
#' @import shinyFiles
#' @import cellranger
#' @author Kirk Gosik <kgosik@broadinstitute.org>
#' @examples
# if cellranger R kit is not installed then install it
if( !{"cellrangerRkit" %in% installed.packages()} ) {
source("http://cf.10xgenomics.com/supp/cell-exp/rkit-install-2.0.0.R")
}
require(cellrangerRkit)
server <- function(input, output, session) {
# defines root directory for the user
shinyFiles::shinyDirChoose(input, 'file_path', roots = c(root = '/'))
# defines root directory for the user
shinyFiles::shinyDirChoose(input, 'data_source', roots = c(root = '/'))
# creates seurat tutorial markdown to html file
observeEvent(input$create_output, {
withProgress(message = "Creating Output File...", {
project_inpt <- gsub(" ", "_", input$project)
home <- normalizePath("/") # normalizes home path
path <- file.path(home, paste(unlist(input$file_path$path[-1]), collapse = .Platform$file.sep))
tissue_inpt <- ifelse(is.null(input$tissue_type), NULL, gsub(" ", "_", input$tissue_type))
celltype_inpt <- ifelse(is.null(input$cell_type), NULL, gsub(" ", "_", input$cell_type))
project_name <- paste0(c(project_inpt,
tissue_inpt,
celltype_inpt,
format(Sys.Date())), collapse = "-")
rmarkdown::render(input = "R/Seurat_to_Markdown.Rmd",
params = list(project = project_name,
path = path,
cells = input$cells,
genes = input$genes,
max_mt = input$max_mt),
output_file = paste0(getwd(), "/output/", project_name, ".html"))
})
})
created_output_path <- reactive({
home <- normalizePath("/") # normalizes home path
path <- file.path(home, paste(unlist(input$data_source$path[-1]), collapse = .Platform$file.sep))
path
})
observe({
updateSelectInput(session,
inputId = "rds_file",
label = "Select RDS file",
choices = gsub(".rds", "", dir(created_output_path(), pattern = ".rds")))
})
## reads in already created seurat object
seurat_obj <- eventReactive(input$read_data, {
withProgress(message = "Loading Data...", {
readRDS(file = dir(created_output_path(), pattern = paste0(input$rds_file, ".rds"), full.names = TRUE))
})
})
outs <- eventReactive(input$read_data, {
# load(file = dir("data", pattern = input$data_source, full.names = TRUE))
# path stored in obj@misc from running Seurat_to_Markdown
selected_path <- seurat_obj()@misc
# reducing Seurat path for Read10x to cellranger expected path for load_cellranger_matrix
outs_pos <- grep("outs", unlist(strsplit(selected_path, "/"))) - 1
selected_path <- file.path(paste(unlist(strsplit(selected_path, "/"))[1:outs_pos], collapse = .Platform$file.sep))
# loads gene - barcode matrix
gbm <- cellrangerRkit::load_cellranger_matrix( selected_path )
# normalize nonzero genes
use_genes <- cellrangerRkit::get_nonzero_genes(gbm)
gbm_bcnorm <- cellrangerRkit::normalize_barcode_sums_to_median(gbm[use_genes, ])
gbm_log <- cellrangerRkit::log_gene_bc_matrix(gbm_bcnorm, base = 10)
# loads analysis results
analysis_results <- cellrangerRkit::load_cellranger_analysis_results( selected_path )
# returns list of the outputs needed for plots
return(list(gbm = gbm,
gbm_log = gbm_log,
tsne_proj = analysis_results$tsne, # tSNE projects from analysis results
clustering = analysis_results$clustering) # clustering from analysis results
)
})
# when input directory is selected updates gene symbols name for selection
observeEvent(!is.null(outs()), {
updateSelectizeInput(session = session,
inputId = "gene_symbol",
label = "Select Gene Symbols",
choices = fData(outs()[["gbm_log"]])$symbol)
})
# calling Modular functions
callModule(module = UMItSNEPlotServer,
id = "tSNE",
outs = outs)
callModule(module = ClusterExplore10xServer,
id = "cluster_explore",
outs = outs)
callModule(module = IdentifytSNEServer,
id = "seurat_out",
obj = seurat_obj)
# callModule(module = MorpheusServer,
# id = "morpheus_out",
# outs = outs)
}
shinyApp(ui = ui, server = server)
kdgosik/scRipt documentation built on May 6, 2019, 8:34 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions server
#' ShinyUI
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' @param id The namespace for the shiny application.
#' @return shinyUI for module
#' @export
#' @import shiny
#' @import shinyFiles
#' @import cellranger
#' @author Kirk Gosik <kgosik@broadinstitute.org>
#' @examples
# if cellranger R kit is not installed then install it
if( !{"cellrangerRkit" %in% installed.packages()} ) {
source("http://cf.10xgenomics.com/supp/cell-exp/rkit-install-2.0.0.R")
}
require(cellrangerRkit)
## comment out the source statements
## comment out the shinyApp() statement at bottom
## change line 110 to take away the ../
# source("ModularUMItSNEPlot.R") ## will move to main part of the package
# source("ModularClusterExplore10x.R") ## will move to main part of the package
# source("ModularIdentifytSNE.R") ## will move to main part of the package
ui <- shinyUI(
fluidPage(
# Application title
titlePanel("Gene Expression Explore"),
# Sidebar with a selector for genes
sidebarLayout(
sidebarPanel(
shiny::radioButtons(inputId = "task",
label = "Select Task",
choices = c("Create Output", "Select Data")),
conditionalPanel(
condition = "input.task == 'Create Output'",
shinyFiles::shinyDirButton(id = "file_path",
label = "10X Path",
title = "Button"),
shiny::p("eg ../filtered_gene_bc_matrices/hg19"),
shiny::textInput("project", "Project Title"),
shiny::textInput("tissue_type", "Tissue Type"),
shiny::textInput("cell_type", "Cell Type (if known)"),
shiny::sliderInput(inputId = "cells",
label = "Minimum Cells Per Gene",
value = 3,
min = 1,
max = 20),
shiny::sliderInput(inputId = "genes",
label = "Minimum Genes Per Cell",
value = 200,
min = 10,
max = 500),
shiny::sliderInput(inputId = "max_mt",
label = "Max Percent Mitochondrial Genes Present",
value = 0.05,
min = 0,
max = 0.5,
step = 0.01),
shiny::actionButton("create_output", "Create Output")
), # conditionalPanel
conditionalPanel(
condition = "input.task == 'Select Data'",
shinyFiles::shinyDirButton(id = "data_source",
label = "Created Output Path",
title = "Button"),
shiny::selectInput(inputId = "rds_file",
label = "Select RDS file",
choices = ""),
shiny::actionButton("read_data", "Read Data"),
shiny::uiOutput("ui_data_load")
) # conditionalPanel
), # sidebarPanel
mainPanel(
tabsetPanel(
tabPanel(title = "Introduction",
includeMarkdown("inst/www/AppIntroduction.md")
), # tabPanel
# Show the t-SNE plot
tabPanel(title = "Cellranger tSNE",
UMItSNEPlotUI("tSNE")
), # tabPanel
tabPanel(title = "Cellranger Cluster",
ClusterExplore10xUI("cluster_explore")
), # tabPanel
tabPanel(title = "Seurat",
textOutput("seurat"),
IdentifytSNEUI("seurat_out")
) # tabPanel
#), # tabPanel
#
# tabPanel(title = "Morpheus",
# MorpheusUI("morpheus_out")
#
# ) # tabPanel
) # tabsetPanel
) # mainPanel
) # sidebarLayout
) # fluidPage
) # shinyUI
#' ShinyServer
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' Runs and visulizes the 10X clustering from the Cell Ranger website
#'
#' @param id shiny id
#' @return shinyUI for module
#' @export
#' @param input List-like object that stores the current values of all of the widgets in your app.
#' @param output List-like object that stores instructions for building the R objects in your app.
#' @param session List-like object about the session to be passed to the UI.
#' @import shiny
#' @import shinyFiles
#' @import cellranger
#' @author Kirk Gosik <kgosik@broadinstitute.org>
#' @examples
# if cellranger R kit is not installed then install it
if( !{"cellrangerRkit" %in% installed.packages()} ) {
source("http://cf.10xgenomics.com/supp/cell-exp/rkit-install-2.0.0.R")
}
require(cellrangerRkit)
server <- function(input, output, session) {
# defines root directory for the user
shinyFiles::shinyDirChoose(input, 'file_path', roots = c(root = '/'))
# defines root directory for the user
shinyFiles::shinyDirChoose(input, 'data_source', roots = c(root = '/'))
# creates seurat tutorial markdown to html file
observeEvent(input$create_output, {
withProgress(message = "Creating Output File...", {
project_inpt <- gsub(" ", "_", input$project)
home <- normalizePath("/") # normalizes home path
path <- file.path(home, paste(unlist(input$file_path$path[-1]), collapse = .Platform$file.sep))
tissue_inpt <- ifelse(is.null(input$tissue_type), NULL, gsub(" ", "_", input$tissue_type))
celltype_inpt <- ifelse(is.null(input$cell_type), NULL, gsub(" ", "_", input$cell_type))
project_name <- paste0(c(project_inpt,
tissue_inpt,
celltype_inpt,
format(Sys.Date())), collapse = "-")
rmarkdown::render(input = "R/Seurat_to_Markdown.Rmd",
params = list(project = project_name,
path = path,
cells = input$cells,
genes = input$genes,
max_mt = input$max_mt),
output_file = paste0(getwd(), "/output/", project_name, ".html"))
})
})
created_output_path <- reactive({
home <- normalizePath("/") # normalizes home path
path <- file.path(home, paste(unlist(input$data_source$path[-1]), collapse = .Platform$file.sep))
path
})
observe({
updateSelectInput(session,
inputId = "rds_file",
label = "Select RDS file",
choices = gsub(".rds", "", dir(created_output_path(), pattern = ".rds")))
})
## reads in already created seurat object
seurat_obj <- eventReactive(input$read_data, {
withProgress(message = "Loading Data...", {
readRDS(file = dir(created_output_path(), pattern = paste0(input$rds_file, ".rds"), full.names = TRUE))
})
})
outs <- eventReactive(input$read_data, {
# load(file = dir("data", pattern = input$data_source, full.names = TRUE))
# path stored in obj@misc from running Seurat_to_Markdown
selected_path <- seurat_obj()@misc
# reducing Seurat path for Read10x to cellranger expected path for load_cellranger_matrix
outs_pos <- grep("outs", unlist(strsplit(selected_path, "/"))) - 1
selected_path <- file.path(paste(unlist(strsplit(selected_path, "/"))[1:outs_pos], collapse = .Platform$file.sep))
# loads gene - barcode matrix
gbm <- cellrangerRkit::load_cellranger_matrix( selected_path )
# normalize nonzero genes
use_genes <- cellrangerRkit::get_nonzero_genes(gbm)
gbm_bcnorm <- cellrangerRkit::normalize_barcode_sums_to_median(gbm[use_genes, ])
gbm_log <- cellrangerRkit::log_gene_bc_matrix(gbm_bcnorm, base = 10)
# loads analysis results
analysis_results <- cellrangerRkit::load_cellranger_analysis_results( selected_path )
# returns list of the outputs needed for plots
return(list(gbm = gbm,
gbm_log = gbm_log,
tsne_proj = analysis_results$tsne, # tSNE projects from analysis results
clustering = analysis_results$clustering) # clustering from analysis results
)
})
# when input directory is selected updates gene symbols name for selection
observeEvent(!is.null(outs()), {
updateSelectizeInput(session = session,
inputId = "gene_symbol",
label = "Select Gene Symbols",
choices = fData(outs()[["gbm_log"]])$symbol)
})
# calling Modular functions
callModule(module = UMItSNEPlotServer,
id = "tSNE",
outs = outs)
callModule(module = ClusterExplore10xServer,
id = "cluster_explore",
outs = outs)
callModule(module = IdentifytSNEServer,
id = "seurat_out",
obj = seurat_obj)
# callModule(module = MorpheusServer,
# id = "morpheus_out",
# outs = outs)
}
shinyApp(ui = ui, server = server)
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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