inst/app/app.R
In bimberlabinternal/ShinySDA: A shiny app to load and browse SDA objects.
# options(repos=structure(BiocManager::repositories()))
# detach("package:Biobase", unload=TRUE)
library(shiny)
library(shinyWidgets)
library(shinydashboard)
# library(shinyjs)
library(shinyFiles)
library(ggplot2)
library(ggrepel)
library(viridis)
library(RColorBrewer)
library(grid)
library(gridExtra)
library(data.table)
library(dplyr)
library(Seurat)
library(SDAtools)
library(Rlabkey)
library(Rdiscvr)
library(roxygen2)
library(rclipboard)
library("BiocParallel")
register(MulticoreParam(4))
library(ShinySDA)
# if (Sys.getenv("SCRATCH_DIR") != "") {
# cachedir <- paste0(Sys.getenv("SCRATCH_DIR"), "ShinySDA-cache")
# } else {
# cachedir <- paste0(Sys.getenv("TMPDIR"), "ShinySDA-cache")
# }
if (Sys.getenv("SCRATCH_DIR") != "") {
init.path = paste0(Sys.getenv("SCRATCH_DIR"), "/data")
} else {
init.path = getwd()
}
# source(system.file('app/fxs.R', package = 'ShinySDA', mustWork = TRUE), local = TRUE)
print(Sys.getenv("SCRATCH_DIR"))
ui <- dashboardPage(skin="red",
dashboardHeader(title = "ShinySDA"),
#https://rstudio.github.io/shinydashboard/appearance.html#icons
dashboardSidebar(
sidebarMenu(
menuItem("Main", tabName = "MainDash", icon = icon("dashboard"), selected = T),
menuItem("Prime-seq Input", tabName = "PrimeSeqInput", icon = icon("dashboard")),
menuItem("Folder Input", tabName = "FolderInput", icon = icon("dashboard")),
menuItem("PreProcessing", tabName = "PreProcess", icon = icon("dashboard")),
menuItem("Run QC", tabName = "QCplots", icon = icon("wrench")),
menuItem("Cell-Score ChiSqr Heatmap w/ Meta", tabName = "ChiSqrHM", icon = icon("wrench")),
menuItem("Cell-Score ChiSqr Export w/ Meta", tabName = "ChiSqrTab", icon = icon("wrench")),
menuItem("Cell-score across w/ Meta", tabName = "CSplots", icon = icon("wrench")),
menuItem("Cell-score boxplots w/ Meta", tabName = "CSBoxPlots", icon = icon("wrench")),
# menuItem("Cell-score tSNE", tabName = "CStSNEPlots", icon = icon("wrench")),
menuItem("Gene-loading Cor HM", tabName = "GL_cor_HM", icon = icon("wrench")),
menuItem("Batch removal", tabName = "BatchRemove", icon = icon("toolbox")),
menuItem("DGE Batch-Removed", tabName = "DGEsda", icon = icon("autoprefixer")),
menuItem("Gene Explorer", tabName = "GeneExplorer", icon = icon("dna")),
menuItem("Save Out", tabName = "SaveOut", icon = icon("save")),
menuItem("@eisamahyari", icon = icon("heart"),
href = "https://eisascience.github.io")
)
),
dashboardBody(
# useShinyjs(),
tags$head(
tags$style(HTML("
.content-wrapper {
background-color: black !important;
}
.main-sidebar {
background-color: black !important;
}
.multicol .shiny-options-group{
-webkit-column-count: 5; /* Chrome, Safari, Opera */
-moz-column-count: 5; /* Firefox */
column-count: 5;
-moz-column-fill: balanced;
-column-fill: balanced;
}
.checkbox{
margin-top: 0px !important;
-webkit-margin-after: 0px !important;
}
"))),
tabItems(
# Main---------------
tabItem(tabName = "MainDash",
h2("Main Dashboard"),
fluidRow(
valueBoxOutput("InfoBox_Main", width = 6),
box(textInput("apiKey", "Prime-seq API Kit",
value =""),
textInput("baseURL", "baseURL",
value ="https://prime-seq.ohsu.edu"),
textInput("defaultFolder", "defPSfold",
value ="Labs/Bimber"),
width = 5, background = "olive"
))),
# Prime-seq input---------
tabItem(tabName = "PrimeSeqInput",
h2("Download from Prime-seq: Use the OutputFileId for an SDA object"),
fluidRow(
valueBoxOutput("InfoBox_Prime", width = 6),
box(textInput("SDA_OFId", "OutputFileId to an SDA Obj",
value ="506842"),
textInput("SDA_PS_save", "path to download and SDA objects",
value ="/Volumes/Maggie/Work/OHSU/Bimber/Expts/RIRA_manuscript/data/sda/primeseq/"),
column(
width = 7,
style = "float: left;",
actionButton("Download_SDA_primeseq", "Download SDA Obj"),
actionButton("Load_SDA_primeseq", "Load SDA Obj"),
actionButton("Down_N_Load_SDA", "** Download & Load **"),
),
# column(
# width = 3,
# style = "float: right;",
# actionButton("DnL_SDA_primeseq", "Do Both", align="right"),
# ),
width = 10, background = "olive"
))),
# Folder input------
tabItem(tabName = "FolderInput",
h2("Folder input: Make sure _MetaDF.rds includes $SubjectId, $ExpID, $EXP.ID, $SampleDate, $SingleR_Labels, $BarcodePrefix"),
fluidRow(
valueBoxOutput("InfoBox_Folder", width = 6),
box(textInput("SDAroot", "Path to SDA folders. Expects dimnames in one dir up.",
value =init.path),
uiOutput("select.folder"),
actionButton("loadSDA", "0. Load SDA"),
width = 10, background = "teal"
))),
# Pre-Process---------
tabItem(tabName = "PreProcess",
h2("Pre-Process the SDA object"),
fluidRow(
valueBoxOutput("InfoBox_PP", width = 6),
box(title = "SpeciesSelect", status = "primary",
solidHeader = TRUE,collapsible = TRUE,
selectInput(inputId = 'species',
label = 'Species',
choices = c('human', 'mouse', 'rhesus'),
selected = , multiple = F),
width = 3, background = "red"
),
box(
# textInput("SDAroot", "Path to SDA folders. Expects dimnames in one dir up.",
# value =init.path),
# uiOutput("select.folder"),
# actionButton("loadSDA", "0. Load SDA"),
actionButton("getGeneAnn", "1. Get Gene Annotations"),
actionButton("getSDAGo", "2. Get SDA GO Enrichments"),
actionButton("runtSNE", "3. Run tSNE (cs-all)"),
actionButton("runtSNEQCfilt", "4.5 Run tSNE (cs-qc)"),
actionButton("runAllProc", "** Run all **"),
# textInput("loadSDAmsg", "File Status", "not loaded"),
width = 10
#fileInput("SDAin", "Browse")
),
box(
title = "QC_MaxScore_filt", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqcMaxScorefilt"),
width = 5, background = "black"
),
box(
title = "tSNE CS All", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_all"),
width = 5, background = "black"
),
box(
title = "tSNE_CS_QC", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_qc"),
width = 5, background = "black"
))),
# QC plots-------
tabItem(tabName = "QCplots",
h2("Full QC plots content"),
fluidRow(
box(
title = "QC1", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc1"),
width = 5, background = "black"
),
box(
title = "QC2", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc2"),
width = 5, background = "black"
),
box(
title = "QC3", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc3"),
width = 5, background = "black"
),
box(
title = "QC4", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc4"),
width = 5, background = "black"
),
box(
title = "QC5", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc5"),
width = 5, background = "black"
),
box(
title = "QC6", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc6"),
width = 5, background = "black"
),
box(
title = "Convergence", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("convergence"),
width = 5, background = "black"
) ,
box(
title = "Gene Loading Hist.", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("loadhist"),
width = 5, background = "black"
) ,
box(
title = "Score Dist.", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("scoredist"),
width = 5, background = "black"
) ,
#The PIP is the mean of the posterior. You can think of it as a measure of how likely it is that this variable is in the true model.
box(
title = "Post. inclus. prob. dist", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("pipdist"),
width = 5, background = "black"
),
box(
title = "Slack-Slab Prior", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("slackslabprior"),
width = 10, background = "black"
)
)
),
# Cell-score Boxplot-------
tabItem(tabName = "CSBoxPlots",
h2("Cell Score Box Plots, scaled to mean = 0"),
fluidRow(
box(
title = "Metadata Selection", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
selectInput("Metaselect5", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
),
box(
title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresBoxplot", height = 1500, width = 900),
width = 10,
background = "black"
)
)
),
# # Cell-score Feature plot-------
# tabItem(tabName = "CStSNEPlots",
# h2("Full Cell Score Feature Plots"),
# fluidRow(
#
# # box(
# # title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
# # collapsible = TRUE,
# # plotOutput("SDAScoresBoxplot", height = 1500, width = 900),
# # width = 10,
# # background = "black"
# # )
# )
# ),
# Cell Score Across plots-------
tabItem(tabName = "CSplots",
h2("Full Cell Score Feature Plots"),
fluidRow(
box(
title = "Metadata Selection", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
selectInput("Metaselect6", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
),
box(
title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresAcross_Legend"),
width = 5,
background = "black"
),
box(
title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresAcross", height = 1500, width = 900),
width = 10,
background = "black"
)
)
),
# ChiSqrTab ------
tabItem(tabName = "ChiSqrTab",
h2("ChiSqr Heatmap Enrichment of Cell-scores per Meta"),
fluidRow(
box(
title = "Select to save", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
checkboxGroupInput("chkbx_MetaSave", "Select items:",
c("Item 1", "Item 2", "Item 3")),
# actionButton("pos_score_save", "Save Pos Score"),
# actionButton("neg_score_save", "Save Neg Score"),
actionButton("upd_score_tabl", "Update Tables"),
),
box(
title = "ChiSqrRes Scores Pos cellscores", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
DT::dataTableOutput("table_SDAScoresChiPos"),
width = 10, background = "light-blue"
),
)
),
# ChiSqrHM --------
tabItem(tabName = "ChiSqrHM",
h2("ChiSqr Heatmap Enrichment of Cell-scores per Meta"),
fluidRow(
box(
title = "Select to plot", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
selectInput("Metaselect4", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
),
box(
title = "ChiSqrRes Scores Pos cellscores", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresChiPos", height = 500),
width = 10, background = "black"
),
box(
title = "ChiSqrRes Scores Neg cellscores", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresChiNeg", height = 500),
width = 10, background = "black"
),
)
),
# Gene-loadig Cor HM-------
tabItem(tabName = "GL_cor_HM",
h2("Gene Loadings Correlation Heatmap"),
fluidRow(
box(
title = "Cor. HM", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GL_Cor_HMplot", height = 500),
width = 10, background = "black"
),
)
),
# Batch removal content----------
tabItem(tabName = "BatchRemove",
h2("Batch Removal"),
fluidRow(
box(
title = "SDA projected on tSNE", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
actionButton("prevSDA_br", "Prev comp"),
actionButton("nextSDA_br", "Next comp"),
plotOutput("SDAtsne_br1"),
width = 5, background = "black"
),
box(
title = "Batch Removal Selection", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
column(10,
uiOutput("CompBatchCheckBoxSelect")
),
actionButton("save_batch_selection", "Save Selection"),
actionButton("load_batch_selection", "Load last Selection"),
actionButton("reset_batch_selection", "Reset last Selection"),
actionButton("select_all_selection", "Select all"),
width=5, background = "black"),
box(
title = "Run tSNE Batch Removed", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
selectInput("tSNEiter", "tSNE n-iter:",
c("Fast-500" = "500",
"Fast2-1000" = "1000",
"Med1-2000" = "2000",
"Med2-5000" = "5000",
"Robust-10000" = "10000",
"OverKill-20000"="20000"), selected = "500"),
selectInput("tSNEpp", "tSNE prplx:",
c("1" = "1",
"10" = "10",
"50-default" = "50",
"100-med" = "100",
"200-max" = "200",
"300-insane!" = "300"), selected = "50"),
actionButton("run_tSNE_CS_batch", "Run tSNE (batch-removed)"),
actionButton("SDAScoresChi_clus", "Show/Hide Pairwise Clustering"),
width = 5, background = "black",
),
box(
title = "tSNE Batch removed", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("DGE_SDA_tSNE"),
width = 10, background = "black"
)
)
),
# DGE-SDA-BatchRemove tab content--------
tabItem(tabName = "DGEsda",
h2("DGE_SDA Batched Removed DGE"),
fluidRow(
box(
title = "tSNE Meta Exploration", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_batch1"),
selectInput("Metaselect1", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
width = 5, background = "black"
),
box(
title = "tSNE Meta Exploration", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_batch2"),
selectInput("Metaselect2", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
width = 5, background = "black"
),
box(
title = "tSNE Meta Exploration", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_batch3"),
selectInput("Metaselect3", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
width = 5, background = "black"
),
box(title = "tSNE SDA projection", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
actionButton("prevSDA_br2", "Prev comp"),
actionButton("nextSDA_br2", "Next comp"),
actionButton("C2Cpos", "Copy2ClipPosGenes"),
actionButton("C2Cneg", "Copy2ClipNegGenes"),
textInput("NoOfGenes", "No. of Genes to output:", "20"),
textInput("SDAVn", "SDA comp. No:"),
plotOutput("SDAtsne_br2"),
width=5, background = "black"
),
box(title = "SDA score tabulation", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAtsne_br2Tab"),
width=10, background = "black"
)
),
box(
title = "Pos. Loadings GO", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GOpos"), #plotlyOutput
width = 5, background = "black"
),
box(
title = "Neg. Loadings GO", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GOneg"),
width = 5, background = "black"
),
box(title = "Pos. Top Genes", status = "info", solidHeader = TRUE, width = 4,
tableOutput("packageTablePos")
),
box(title = "Neg. Top Genes", status = "info", solidHeader = TRUE, width = 4,
tableOutput("packageTableNeg")
)
),
# Batch-Removed Exploration--------
tabItem(tabName = "GeneExplorer",
h2("DGE_SDA Batched Removed DGE Explorer"),
fluidRow(
box(
title = "Inputs", status = "warning", solidHeader = TRUE,
"Multiple formatting of gene sets accepted",
br(), "List can be seperated by comma e.g. from ",
br(), " or spaces e.g. from Excel",
br(), "Also, single or double quotes or not",
#sliderInput("ComponentN", "Slider input:", 1, 150, 1),
textInput("GeneSet", "A set of genes", "'CD19', 'CD20', 'MS4A1', 'IGHM', 'IGHA2'"),
width = 5
),
box(
title = "BatchRemoved-DGE Expr", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GeneExprSDAtSNE"),
width = 5
),
box(
title = "Positive Loadings", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GenesEnrichSDAPos"),
width = 10
),
box(
title = "Negative Loadings", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GenesEnrichSDANeg"),
width = 10
)
)
),
# Save out----------
tabItem(tabName = "SaveOut",
h2("Save the results for downstream analysis"),
fluidRow(
box(
title = "Save as Seurat Object", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
actionButton("SaveAsSerObj", "Save as Seurat Obj"),
width = 5, background = "black"
)))
) #end of tabItems
) #end of body
) #end UI
# Server --------
server <- function(input, output, session) {
## loading local files
shinyFileChoose(input,'file', session=session,roots=c(wd='.'))
## environment defaults
envv=reactiveValues(y=NULL)
envv$InfoBox_sub = "Load in SDA, use either the Prime-seq or Folder input tabs"
## controls how to handle pipe depending on data
envv$Origin = "unk"
## Feature Enrichment; used in returning enrichment profile from chi sqr analysis
# envv$FeatEnrich$pos = list()
# envv$FeatEnrich$neg = list()
# Use the try() function to run the function and handle the error
result <- try(source("apik.R",local = TRUE), silent = TRUE)
# Check if an error occurred
if (inherits(result, "try-error")) {
# either make apik.R and put your api key in it as envv$apik = "" or type it directly
} else {
# The function ran successfully. Use the result here.
source("apik.R",local = TRUE)
updateTextInput(session, "apiKey", value = isolate(envv$apik))
}
### SDA local folder
output$select.folder <-
renderUI(expr = selectInput(inputId = 'folder.name',
label = 'Folder Name',
choices = list.dirs(path = input$SDAroot,
full.names = FALSE,
recursive = FALSE)))
source("app_Theme.R",local = TRUE)
source("app_InfoBox.R",local = TRUE)
# source("fxs.R",local = TRUE)
## ObserveEvents--------------------------------------
source("app_OE.R",local = TRUE)
source("app_OE_load.R",local = TRUE)
source("app_OE_biomart.R",local = TRUE)
source("app_OE_GO.R",local = TRUE)
source("app_OE_tSNE.R",local = TRUE)
## Plots--------------------------------------
source("app_Figs.R",local = TRUE)
## QC tabs--------------------------------------
source("app_Figs_ChiSqr.R",local = TRUE)
source("app_Figs_QC.R",local = TRUE)
## Batch removal tab--------------------------------------
source("app_OE_BatchRemoval.R",local = TRUE)
output$CompBatchCheckBoxSelect <- renderUI({
choice <- 1:as.numeric(envv$SDAres$command_arguments$num_comps) #paste0("SDA", 1:as.numeric(envv$SDAres$command_arguments$num_comps)) # envv$QC_components
if(is.null(envv$Remove_comps)){
selected <- setdiff(choice, envv$QC_components) #setdiff(choice, paste0("SDA",envv$QC_components))
} else {
selected <- envv$Remove_comps
}
tags$div(align = 'left',
class = 'multicol',
checkboxGroupInput("CompBatchCheckBoxSelect", "components",
choices=choice, selected = selected))
})
## Batch Removed DGE --------------------------------------
source("app_OE_BatchRemoved.R",local = TRUE)
output$packageTablePos <- renderTable({
print_gene_list(results=envv$SDAres, as.numeric(envv$QC_compIter), PosOnly = T) %>%
as.data.frame() %>%
head(as.numeric(input$NoOfGenes))
}, digits = 1)
output$packageTableNeg <- renderTable({
print_gene_list(results=envv$SDAres, as.numeric(envv$QC_compIter), NegOnly = T) %>%
as.data.frame() %>%
head(as.numeric(input$NoOfGenes))
}, digits = 1)
## Enrich N Explore-----------
## SAve out ------------
source("app_OE_SaveOut.R",local = TRUE)
}
shinyApp(ui, server)
bimberlabinternal/ShinySDA documentation built on Feb. 5, 2023, 7:09 a.m.
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# options(repos=structure(BiocManager::repositories()))
# detach("package:Biobase", unload=TRUE)
library(shiny)
library(shinyWidgets)
library(shinydashboard)
# library(shinyjs)
library(shinyFiles)
library(ggplot2)
library(ggrepel)
library(viridis)
library(RColorBrewer)
library(grid)
library(gridExtra)
library(data.table)
library(dplyr)
library(Seurat)
library(SDAtools)
library(Rlabkey)
library(Rdiscvr)
library(roxygen2)
library(rclipboard)
library("BiocParallel")
register(MulticoreParam(4))
library(ShinySDA)
# if (Sys.getenv("SCRATCH_DIR") != "") {
# cachedir <- paste0(Sys.getenv("SCRATCH_DIR"), "ShinySDA-cache")
# } else {
# cachedir <- paste0(Sys.getenv("TMPDIR"), "ShinySDA-cache")
# }
if (Sys.getenv("SCRATCH_DIR") != "") {
init.path = paste0(Sys.getenv("SCRATCH_DIR"), "/data")
} else {
init.path = getwd()
}
# source(system.file('app/fxs.R', package = 'ShinySDA', mustWork = TRUE), local = TRUE)
print(Sys.getenv("SCRATCH_DIR"))
ui <- dashboardPage(skin="red",
dashboardHeader(title = "ShinySDA"),
#https://rstudio.github.io/shinydashboard/appearance.html#icons
dashboardSidebar(
sidebarMenu(
menuItem("Main", tabName = "MainDash", icon = icon("dashboard"), selected = T),
menuItem("Prime-seq Input", tabName = "PrimeSeqInput", icon = icon("dashboard")),
menuItem("Folder Input", tabName = "FolderInput", icon = icon("dashboard")),
menuItem("PreProcessing", tabName = "PreProcess", icon = icon("dashboard")),
menuItem("Run QC", tabName = "QCplots", icon = icon("wrench")),
menuItem("Cell-Score ChiSqr Heatmap w/ Meta", tabName = "ChiSqrHM", icon = icon("wrench")),
menuItem("Cell-Score ChiSqr Export w/ Meta", tabName = "ChiSqrTab", icon = icon("wrench")),
menuItem("Cell-score across w/ Meta", tabName = "CSplots", icon = icon("wrench")),
menuItem("Cell-score boxplots w/ Meta", tabName = "CSBoxPlots", icon = icon("wrench")),
# menuItem("Cell-score tSNE", tabName = "CStSNEPlots", icon = icon("wrench")),
menuItem("Gene-loading Cor HM", tabName = "GL_cor_HM", icon = icon("wrench")),
menuItem("Batch removal", tabName = "BatchRemove", icon = icon("toolbox")),
menuItem("DGE Batch-Removed", tabName = "DGEsda", icon = icon("autoprefixer")),
menuItem("Gene Explorer", tabName = "GeneExplorer", icon = icon("dna")),
menuItem("Save Out", tabName = "SaveOut", icon = icon("save")),
menuItem("@eisamahyari", icon = icon("heart"),
href = "https://eisascience.github.io")
)
),
dashboardBody(
# useShinyjs(),
tags$head(
tags$style(HTML("
.content-wrapper {
background-color: black !important;
}
.main-sidebar {
background-color: black !important;
}
.multicol .shiny-options-group{
-webkit-column-count: 5; /* Chrome, Safari, Opera */
-moz-column-count: 5; /* Firefox */
column-count: 5;
-moz-column-fill: balanced;
-column-fill: balanced;
}
.checkbox{
margin-top: 0px !important;
-webkit-margin-after: 0px !important;
}
"))),
tabItems(
# Main---------------
tabItem(tabName = "MainDash",
h2("Main Dashboard"),
fluidRow(
valueBoxOutput("InfoBox_Main", width = 6),
box(textInput("apiKey", "Prime-seq API Kit",
value =""),
textInput("baseURL", "baseURL",
value ="https://prime-seq.ohsu.edu"),
textInput("defaultFolder", "defPSfold",
value ="Labs/Bimber"),
width = 5, background = "olive"
))),
# Prime-seq input---------
tabItem(tabName = "PrimeSeqInput",
h2("Download from Prime-seq: Use the OutputFileId for an SDA object"),
fluidRow(
valueBoxOutput("InfoBox_Prime", width = 6),
box(textInput("SDA_OFId", "OutputFileId to an SDA Obj",
value ="506842"),
textInput("SDA_PS_save", "path to download and SDA objects",
value ="/Volumes/Maggie/Work/OHSU/Bimber/Expts/RIRA_manuscript/data/sda/primeseq/"),
column(
width = 7,
style = "float: left;",
actionButton("Download_SDA_primeseq", "Download SDA Obj"),
actionButton("Load_SDA_primeseq", "Load SDA Obj"),
actionButton("Down_N_Load_SDA", "** Download & Load **"),
),
# column(
# width = 3,
# style = "float: right;",
# actionButton("DnL_SDA_primeseq", "Do Both", align="right"),
# ),
width = 10, background = "olive"
))),
# Folder input------
tabItem(tabName = "FolderInput",
h2("Folder input: Make sure _MetaDF.rds includes $SubjectId, $ExpID, $EXP.ID, $SampleDate, $SingleR_Labels, $BarcodePrefix"),
fluidRow(
valueBoxOutput("InfoBox_Folder", width = 6),
box(textInput("SDAroot", "Path to SDA folders. Expects dimnames in one dir up.",
value =init.path),
uiOutput("select.folder"),
actionButton("loadSDA", "0. Load SDA"),
width = 10, background = "teal"
))),
# Pre-Process---------
tabItem(tabName = "PreProcess",
h2("Pre-Process the SDA object"),
fluidRow(
valueBoxOutput("InfoBox_PP", width = 6),
box(title = "SpeciesSelect", status = "primary",
solidHeader = TRUE,collapsible = TRUE,
selectInput(inputId = 'species',
label = 'Species',
choices = c('human', 'mouse', 'rhesus'),
selected = , multiple = F),
width = 3, background = "red"
),
box(
# textInput("SDAroot", "Path to SDA folders. Expects dimnames in one dir up.",
# value =init.path),
# uiOutput("select.folder"),
# actionButton("loadSDA", "0. Load SDA"),
actionButton("getGeneAnn", "1. Get Gene Annotations"),
actionButton("getSDAGo", "2. Get SDA GO Enrichments"),
actionButton("runtSNE", "3. Run tSNE (cs-all)"),
actionButton("runtSNEQCfilt", "4.5 Run tSNE (cs-qc)"),
actionButton("runAllProc", "** Run all **"),
# textInput("loadSDAmsg", "File Status", "not loaded"),
width = 10
#fileInput("SDAin", "Browse")
),
box(
title = "QC_MaxScore_filt", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqcMaxScorefilt"),
width = 5, background = "black"
),
box(
title = "tSNE CS All", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_all"),
width = 5, background = "black"
),
box(
title = "tSNE_CS_QC", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_qc"),
width = 5, background = "black"
))),
# QC plots-------
tabItem(tabName = "QCplots",
h2("Full QC plots content"),
fluidRow(
box(
title = "QC1", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc1"),
width = 5, background = "black"
),
box(
title = "QC2", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc2"),
width = 5, background = "black"
),
box(
title = "QC3", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc3"),
width = 5, background = "black"
),
box(
title = "QC4", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc4"),
width = 5, background = "black"
),
box(
title = "QC5", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc5"),
width = 5, background = "black"
),
box(
title = "QC6", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAqc6"),
width = 5, background = "black"
),
box(
title = "Convergence", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("convergence"),
width = 5, background = "black"
) ,
box(
title = "Gene Loading Hist.", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("loadhist"),
width = 5, background = "black"
) ,
box(
title = "Score Dist.", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("scoredist"),
width = 5, background = "black"
) ,
#The PIP is the mean of the posterior. You can think of it as a measure of how likely it is that this variable is in the true model.
box(
title = "Post. inclus. prob. dist", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("pipdist"),
width = 5, background = "black"
),
box(
title = "Slack-Slab Prior", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("slackslabprior"),
width = 10, background = "black"
)
)
),
# Cell-score Boxplot-------
tabItem(tabName = "CSBoxPlots",
h2("Cell Score Box Plots, scaled to mean = 0"),
fluidRow(
box(
title = "Metadata Selection", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
selectInput("Metaselect5", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
),
box(
title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresBoxplot", height = 1500, width = 900),
width = 10,
background = "black"
)
)
),
# # Cell-score Feature plot-------
# tabItem(tabName = "CStSNEPlots",
# h2("Full Cell Score Feature Plots"),
# fluidRow(
#
# # box(
# # title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
# # collapsible = TRUE,
# # plotOutput("SDAScoresBoxplot", height = 1500, width = 900),
# # width = 10,
# # background = "black"
# # )
# )
# ),
# Cell Score Across plots-------
tabItem(tabName = "CSplots",
h2("Full Cell Score Feature Plots"),
fluidRow(
box(
title = "Metadata Selection", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
selectInput("Metaselect6", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
),
box(
title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresAcross_Legend"),
width = 5,
background = "black"
),
box(
title = "Scores order by Meta", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresAcross", height = 1500, width = 900),
width = 10,
background = "black"
)
)
),
# ChiSqrTab ------
tabItem(tabName = "ChiSqrTab",
h2("ChiSqr Heatmap Enrichment of Cell-scores per Meta"),
fluidRow(
box(
title = "Select to save", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
checkboxGroupInput("chkbx_MetaSave", "Select items:",
c("Item 1", "Item 2", "Item 3")),
# actionButton("pos_score_save", "Save Pos Score"),
# actionButton("neg_score_save", "Save Neg Score"),
actionButton("upd_score_tabl", "Update Tables"),
),
box(
title = "ChiSqrRes Scores Pos cellscores", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
DT::dataTableOutput("table_SDAScoresChiPos"),
width = 10, background = "light-blue"
),
)
),
# ChiSqrHM --------
tabItem(tabName = "ChiSqrHM",
h2("ChiSqr Heatmap Enrichment of Cell-scores per Meta"),
fluidRow(
box(
title = "Select to plot", status = "primary", solidHeader = TRUE,
collapsible = TRUE, background = "black",
selectInput("Metaselect4", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
),
box(
title = "ChiSqrRes Scores Pos cellscores", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresChiPos", height = 500),
width = 10, background = "black"
),
box(
title = "ChiSqrRes Scores Neg cellscores", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAScoresChiNeg", height = 500),
width = 10, background = "black"
),
)
),
# Gene-loadig Cor HM-------
tabItem(tabName = "GL_cor_HM",
h2("Gene Loadings Correlation Heatmap"),
fluidRow(
box(
title = "Cor. HM", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GL_Cor_HMplot", height = 500),
width = 10, background = "black"
),
)
),
# Batch removal content----------
tabItem(tabName = "BatchRemove",
h2("Batch Removal"),
fluidRow(
box(
title = "SDA projected on tSNE", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
actionButton("prevSDA_br", "Prev comp"),
actionButton("nextSDA_br", "Next comp"),
plotOutput("SDAtsne_br1"),
width = 5, background = "black"
),
box(
title = "Batch Removal Selection", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
column(10,
uiOutput("CompBatchCheckBoxSelect")
),
actionButton("save_batch_selection", "Save Selection"),
actionButton("load_batch_selection", "Load last Selection"),
actionButton("reset_batch_selection", "Reset last Selection"),
actionButton("select_all_selection", "Select all"),
width=5, background = "black"),
box(
title = "Run tSNE Batch Removed", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
selectInput("tSNEiter", "tSNE n-iter:",
c("Fast-500" = "500",
"Fast2-1000" = "1000",
"Med1-2000" = "2000",
"Med2-5000" = "5000",
"Robust-10000" = "10000",
"OverKill-20000"="20000"), selected = "500"),
selectInput("tSNEpp", "tSNE prplx:",
c("1" = "1",
"10" = "10",
"50-default" = "50",
"100-med" = "100",
"200-max" = "200",
"300-insane!" = "300"), selected = "50"),
actionButton("run_tSNE_CS_batch", "Run tSNE (batch-removed)"),
actionButton("SDAScoresChi_clus", "Show/Hide Pairwise Clustering"),
width = 5, background = "black",
),
box(
title = "tSNE Batch removed", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("DGE_SDA_tSNE"),
width = 10, background = "black"
)
)
),
# DGE-SDA-BatchRemove tab content--------
tabItem(tabName = "DGEsda",
h2("DGE_SDA Batched Removed DGE"),
fluidRow(
box(
title = "tSNE Meta Exploration", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_batch1"),
selectInput("Metaselect1", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
width = 5, background = "black"
),
box(
title = "tSNE Meta Exploration", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_batch2"),
selectInput("Metaselect2", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
width = 5, background = "black"
),
box(
title = "tSNE Meta Exploration", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("tSNE_CS_batch3"),
selectInput("Metaselect3", "Meta select:",
c("Population" = "Population",
"SampleDate" = "SampleDate",
"SubjectId" = "SubjectId",
"Phase" = "Phase"), selected = "Population"),
width = 5, background = "black"
),
box(title = "tSNE SDA projection", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
actionButton("prevSDA_br2", "Prev comp"),
actionButton("nextSDA_br2", "Next comp"),
actionButton("C2Cpos", "Copy2ClipPosGenes"),
actionButton("C2Cneg", "Copy2ClipNegGenes"),
textInput("NoOfGenes", "No. of Genes to output:", "20"),
textInput("SDAVn", "SDA comp. No:"),
plotOutput("SDAtsne_br2"),
width=5, background = "black"
),
box(title = "SDA score tabulation", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("SDAtsne_br2Tab"),
width=10, background = "black"
)
),
box(
title = "Pos. Loadings GO", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GOpos"), #plotlyOutput
width = 5, background = "black"
),
box(
title = "Neg. Loadings GO", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GOneg"),
width = 5, background = "black"
),
box(title = "Pos. Top Genes", status = "info", solidHeader = TRUE, width = 4,
tableOutput("packageTablePos")
),
box(title = "Neg. Top Genes", status = "info", solidHeader = TRUE, width = 4,
tableOutput("packageTableNeg")
)
),
# Batch-Removed Exploration--------
tabItem(tabName = "GeneExplorer",
h2("DGE_SDA Batched Removed DGE Explorer"),
fluidRow(
box(
title = "Inputs", status = "warning", solidHeader = TRUE,
"Multiple formatting of gene sets accepted",
br(), "List can be seperated by comma e.g. from ",
br(), " or spaces e.g. from Excel",
br(), "Also, single or double quotes or not",
#sliderInput("ComponentN", "Slider input:", 1, 150, 1),
textInput("GeneSet", "A set of genes", "'CD19', 'CD20', 'MS4A1', 'IGHM', 'IGHA2'"),
width = 5
),
box(
title = "BatchRemoved-DGE Expr", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GeneExprSDAtSNE"),
width = 5
),
box(
title = "Positive Loadings", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GenesEnrichSDAPos"),
width = 10
),
box(
title = "Negative Loadings", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
plotOutput("GenesEnrichSDANeg"),
width = 10
)
)
),
# Save out----------
tabItem(tabName = "SaveOut",
h2("Save the results for downstream analysis"),
fluidRow(
box(
title = "Save as Seurat Object", status = "primary", solidHeader = TRUE,
collapsible = TRUE,
actionButton("SaveAsSerObj", "Save as Seurat Obj"),
width = 5, background = "black"
)))
) #end of tabItems
) #end of body
) #end UI
# Server --------
server <- function(input, output, session) {
## loading local files
shinyFileChoose(input,'file', session=session,roots=c(wd='.'))
## environment defaults
envv=reactiveValues(y=NULL)
envv$InfoBox_sub = "Load in SDA, use either the Prime-seq or Folder input tabs"
## controls how to handle pipe depending on data
envv$Origin = "unk"
## Feature Enrichment; used in returning enrichment profile from chi sqr analysis
# envv$FeatEnrich$pos = list()
# envv$FeatEnrich$neg = list()
# Use the try() function to run the function and handle the error
result <- try(source("apik.R",local = TRUE), silent = TRUE)
# Check if an error occurred
if (inherits(result, "try-error")) {
# either make apik.R and put your api key in it as envv$apik = "" or type it directly
} else {
# The function ran successfully. Use the result here.
source("apik.R",local = TRUE)
updateTextInput(session, "apiKey", value = isolate(envv$apik))
}
### SDA local folder
output$select.folder <-
renderUI(expr = selectInput(inputId = 'folder.name',
label = 'Folder Name',
choices = list.dirs(path = input$SDAroot,
full.names = FALSE,
recursive = FALSE)))
source("app_Theme.R",local = TRUE)
source("app_InfoBox.R",local = TRUE)
# source("fxs.R",local = TRUE)
## ObserveEvents--------------------------------------
source("app_OE.R",local = TRUE)
source("app_OE_load.R",local = TRUE)
source("app_OE_biomart.R",local = TRUE)
source("app_OE_GO.R",local = TRUE)
source("app_OE_tSNE.R",local = TRUE)
## Plots--------------------------------------
source("app_Figs.R",local = TRUE)
## QC tabs--------------------------------------
source("app_Figs_ChiSqr.R",local = TRUE)
source("app_Figs_QC.R",local = TRUE)
## Batch removal tab--------------------------------------
source("app_OE_BatchRemoval.R",local = TRUE)
output$CompBatchCheckBoxSelect <- renderUI({
choice <- 1:as.numeric(envv$SDAres$command_arguments$num_comps) #paste0("SDA", 1:as.numeric(envv$SDAres$command_arguments$num_comps)) # envv$QC_components
if(is.null(envv$Remove_comps)){
selected <- setdiff(choice, envv$QC_components) #setdiff(choice, paste0("SDA",envv$QC_components))
} else {
selected <- envv$Remove_comps
}
tags$div(align = 'left',
class = 'multicol',
checkboxGroupInput("CompBatchCheckBoxSelect", "components",
choices=choice, selected = selected))
})
## Batch Removed DGE --------------------------------------
source("app_OE_BatchRemoved.R",local = TRUE)
output$packageTablePos <- renderTable({
print_gene_list(results=envv$SDAres, as.numeric(envv$QC_compIter), PosOnly = T) %>%
as.data.frame() %>%
head(as.numeric(input$NoOfGenes))
}, digits = 1)
output$packageTableNeg <- renderTable({
print_gene_list(results=envv$SDAres, as.numeric(envv$QC_compIter), NegOnly = T) %>%
as.data.frame() %>%
head(as.numeric(input$NoOfGenes))
}, digits = 1)
## Enrich N Explore-----------
## SAve out ------------
source("app_OE_SaveOut.R",local = TRUE)
}
shinyApp(ui, server)
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