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server.R
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server.R
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library(plyr)
library(ggplot2)
library(RColorBrewer)
library(reshape2)
library(gtools)
library(stats)
library(shiny)
library(scales)
library(plotly)
## library(httr)
library(shinyTree)
library(jsonlite)
library(DT)
library(shinyjs)
library(stringr)
## library(parallel)
library(DBI)
library(odbc)
shinyServer(function(input,output,session){
## tsne.data <- readRDS('../../results/recount/tsne/recount_tsne_list_pca_noNAs_pcinit_eta200_over50_pc3sd_poscounts_log.RDS')[['30.50']]
## tsne.data <- readRDS('data/tsne_recount_pc3sd_poscounts_p175_nv750.RDS')
## tsne.data <- readRDS('../../results/recount/tmp/tsne_over50_poscounts_log_combp_30_250.RDS')
## tsne.data <- readRDS('data/recount_tsne_pca_noNAs_pcinit_eta2875_over50_pc3sd_tpm_log_p60_nv750.RDS')
## tsne.data <- readRDS('../../results/recount/tsne/recount_tsne_list_pca_pcinit_eta2875_over50_pc3sd_tpm_log_90th_var_genes.RDS')[['40.100']]
## tsne.data <- readRDS('../../results/recount/tsne/recount_tsne_list_pca_noNAs_pcinit_eta2875_over50_pc3sd_tpm_log.RDS')[['60.100']]
tsne.data <- readRDS('data/recount_tsne_pca_pcinit_eta2875_over50_pc3sd_tpm_log_90th_var_genes_p40_nv100.RDS')
## tsne.data <- tsne.data + matrix(data=rnorm(2*nrow(tsne.data),sd=0.5),ncol=2)
tsne.order <- rownames(tsne.data)
## tsne.meta <- readRDS('data/recount2_meta_edited_hist_pc3sd_over50.RDS')
tsne.meta <- readRDS('data/recount2_meta_edited_hover_labels.RDS')
## tsne.meta <- readRDS('data/recount_meta_sampletype_urls.RDS')
## rownames(tsne.meta) <- tsne.meta$run_id
## tsne.meta <- tsne.meta[tsne.order,]
## tcga.gtex.meta <- readRDS('data/tcga_gtex_meta_edited_histologies.RDS')
## rownames(tcga.gtex.meta) <- tcga.gtex.meta$data_id
## tcga.gtex.meta <- tcga.gtex.meta[tsne.order,]
## tsne.meta <- cbind(tsne.meta,tcga.gtex.meta[,c('tissue_general','tissue_detail')])
gene.tpm.samps <- readRDS('data/mrmnorm_mat_rownames.RDS')
gene.choices <- readRDS('data/shiny_gene_choice_list.RDS')
gene.num.vec <- readRDS('data/shiny_gene_num_vec.RDS')
## louvain.dat <- read.table('../../results/recount/clustering/leiden_rsweep_pca_over50_pc3sd_tpm_log_nv100_narrow_90th_var_genes_k30_sim.tsv',sep='\t',row.names=1)
## ## colnames(louvain.dat) <- c('0.1', '0.075', '0.05', '0.025', '0.01', '0.0075', '0.005', '0.0025', '0.001', '0.00075', '0.0005', '0.00025', '0.00001')
## ## colnames(louvain.dat) <- c('0.1','0.11','0.15','0.175','0.2')
## colnames(louvain.dat) <- c('0.007', '0.0075', '0.008', '0.0085', '0.009', '0.0095', '0.01', '0.0105', '0.011', '0.0115', '0.012', '0.0125', '0.013')
## louvain.dat <- read.table('../../results/recount/clustering/leiden_rsweep_narrow_pca_over50_pc3sd_tpm_log_k20_sim.tsv',sep='\t',row.names=1)
## louvain.dat <- read.table('../../results/recount/clustering/leiden_rsweep_narrow_pca_over50_pc3sd_tpm_log_nv100_k30_sim.tsv',sep='\t',row.names=1)
## ## colnames(louvain.dat) <- c('0.005','0.0045','0.004','0.0035','0.003','0.0025')
## colnames(louvain.dat) <- c('0.03','0.0275','0.025','0.0225','0.02','0.0175','0.015','0.0125','0.01')
## colnames(louvain.dat) <- c('0.1', '0.075', '0.05', '0.025', '0.01', '0.0075', '0.005', '0.0025', '0.001', '0.00075', '0.0005', '0.00025', '0.00001')
## louvain.vec <- louvain.dat[,'0.009']
## names(louvain.vec) <- tsne.order
louvain.vec <- readRDS('data/leiden_r9e-3_over50_pc3sd_tpm_log_k30_sim_90th_var_genes.RDS')
## louvain.vec <- readRDS('data/leiden_r25e-3_over50_pc3sd_poscounts_k40_sim_nosingles.RDS')
## louvain.vec <- readRDS('data/leiden_pca_r5e-3_pc3sd_tpm_log_k20_sim_nosingles.RDS')
## louvain.vec <- readRDS('data/leiden_r25e-3_pc3sd_tpm_log_k40_sim_nosingles.RDS')
## louvain.vec <- readRDS('data/leiden_r9e-3_over50_pc3sd_tpm_log_k30_sim_90th_var_genes.RDS')
louvain.choices <- sort(unique(louvain.vec))
louvain.choices <- sapply(louvain.choices,function(x) sprintf('Louvain Cluster %s',x))
names(louvain.choices) <- louvain.choices
cellmarker.info <- readRDS('data/cell_marker_gene_table_fixed_ens.RDS')
rownames(cellmarker.info) <- cellmarker.info$V3
cellmarker.annotation.counts <- readRDS('data/cell_marker_annotations_marker_counts.RDS')
## wgcna.dat <- readRDS('data/wgcna_app_table_pos_log_pc3sd_min100_ds2.RDS')
## onevent('item_remove','hooHa-selectized',print('bar'))
user.selections <- reactiveValues(
selection.list = list(),
selection.datalist = data.frame(),
gene.input.results = list(),
gene.input.datalist = data.frame(),
tsne.traces = list(tsne.order),
previous.tab = 't-SNE',
violinX.change = TRUE,
colorButtonActive = FALSE,
currentViolinGroups = c(),
violinGroupRendered = FALSE,
firstViolinRender = FALSE
)
con <- dbConnect(odbc::odbc(),'Mercator PostGres Unicode')
updateSelectizeInput(session,
'whichGene',
choices=gene.choices,
server=TRUE,
options=list(maxOptions=10,
closeAfterSelect=TRUE
)
)
onevent('change','violinXFactors',function(event){
isolate({user.selections$violinX.change <- TRUE})
})
## updateSelectizeInput(session,
## 'hooHa',
## choices=c(1,2,3,4,5),
## selected=c(1,2),
## server=TRUE,
## options=list(maxOptions=10,
## closeAfterSelect=FALSE)
## )
projection.getDatalist <- reactive({
input$gene.vec
if(length(user.selections$gene.input.results) == 0){
## return(data.frame('name'=c(),'min'=c()))
return(subset(data.frame('name'=c(1,2),'min'=c(2,3)),name>3))
}
else{
return(user.selections$gene.input.datalist)
}
})
selection.getDatalist <- reactive({
input$saveSelection
## print('get datalist')
## print(user.selections$selection.list)
if(length(user.selections$selection.list) == 0){
## return(data.frame('name'='demo','length'=0))
## return(data.frame('name'=c(),'length'=c()))
return(subset(data.frame('name'=c(1,2),'length'=c(2,3)),name>3))
}
else{
return(user.selections$selection.datalist)
}
})
observeEvent(input$barPlotFactor, {
if(grepl('Louvain', input$barPlotFactor)){
updateSelectInput(session,
'barPlotXaxis',
label='Bar Plot X-axis',
choices = c('Project ID' = 'proj_id',
'GTEx/TCGA Gross Tissue' = 'tissue_general',
'GTEx/TCGA Detailed Tissue' = 'tissue_detail',
'Sample Type' = 'sample_type',
'Mesh: Anatomy' = 'Mesh',
'Tissue' = 'Tissue',
'DOID' = 'DOID',
'EFO: Cultured Cells'='efo',
'Louvain' = 'Louvain',
'Marker Gene Tissue Types'='marker_tissue_type',
'Marker Gene Cancer Type' = 'marker_cancer_type',
'Marker Gene Cell Type' = 'marker_cell_type',
'Marker Gene Cell Name' = 'marker_cell_name')
)
} else{
updateSelectInput(session,
'barPlotXaxis',
label='Bar Plot X-axis',
choices = c('No Coloring' = 'No Coloring',
'Project ID' = 'proj_id',
'GTEx/TCGA Gross Tissue' = 'tissue_general',
'GTEx/TCGA Detailed Tissue' = 'tissue_detail',
'Sample Type' = 'sample_type',
'Mesh: Anatomy' = 'Mesh',
'Tissue' = 'Tissue',
'DOID' = 'DOID',
'EFO: Cultured Cells'='efo',
'Louvain' = 'Louvain')
)
}
})
observeEvent(input$wgcnaGeneTable_rows_selected, {
selected.gene <- getWgcnaGeneTable()[input$wgcnaGeneTable_rows_selected,3]
updateSelectizeInput(session,
'whichGene',
choices = gene.choices,
server=T,
options=list(maxOptions=10,
closeAfterSelect=T
),
selected=gene.choices[gene.num.vec[selected.gene]]
)
})
observeEvent(input$geneTable_rows_selected, {
## if(input$geneGroup == 'all'){
## ## selected.marker <- rownames(marker.list[['all']])[input$geneTable_rows_selected]
## }
## else{
## selected.marker <- rownames(marker.list[[as.double(input$geneGroup)+1]])[input$geneTable_rows_selected]
## }
selected.marker <- rownames(getGeneTable())[input$geneTable_rows_selected]
## print(selected.marker)
updateSelectizeInput(session,
'whichGene',
choices=gene.choices,
server=T,
options=list(maxOptions=10,
closeAfterSelect=T
),
selected=gene.choices[gene.num.vec[selected.marker]]
)
})
observeEvent(input$saveSelection, {
event.data <- event_data('plotly_selected',source = 'tsne')
## saveRDS(event.data,'~/Documents/Projects/Mercator/tmp/event_dat.RDS')
if(is.null(event.data) == TRUE) return(NULL)
## curveNumber <- event.data$curveNumber+1
## inds <- event.data$pointNumber+1
selection.vec <- c()
for(curveNum in unique(event.data$curveNumber)){
inds <- subset(event.data,curveNumber==curveNum)$pointNumber + 1
selection.vec <- c(selection.vec,user.selections$tsne.traces[[curveNum+1]][inds])
}
## user.selections$selection.list[[length(user.selections$selection.list)+1]] <- user.selections$tsne.traces[[curveNumber[1]]][inds]
user.selections$selection.list[[length(user.selections$selection.list)+1]] <- selection.vec
## user.selections$selection.list[[length(user.selections$selection.list)+1]] <- data.frame(curveNumber,inds)
## print(length(user.selections$selection.list))
label <- input$selectionName
if(label == ''){
label <- sprintf('Selection %d',length(user.selections$selection.list))
}
user.selections$selection.datalist <- rbind(user.selections$selection.datalist,data.frame('name'=label,'length'=nrow(event.data)))
})
output$sampleInputTable <- DT::renderDT({
datalist <- projection.getDatalist()
dataDT <- DT::datatable(datalist,
selection='single',
options= list(
searching=FALSE,
paging=FALSE,
info=FALSE)
)
return(dataDT)
})
output$wgcnaGeneTable <- DT::renderDT({
wgcna.tab <- getWgcnaGeneTable()
## dataDT <- DT::datatable(wgcna.tab[,c(11,9,10,4,5,6,7,8)],
dataDT <- DT::datatable(wgcna.tab[,c(11,9,10,4)],
selection='single',
options=list(
'searching'=TRUE,
'legnthChange'=FALSE,
'pagingType'='full',
'autoWidth'=TRUE,
'pageLength'=25),
escape=FALSE,
rownames=FALSE
)
return(dataDT)
})
output$wgcnaGoTable <- DT::renderDT({
go.tab <- getWgcnaGoTable()
dataDT <- DT::datatable(go.tab,
selection='none',
options=list(
'searching'=TRUE,
'legnthChange'=FALSE,
'pagingType'='full',
'autoWidth'=TRUE,
'pageLength'=25),
escape=FALSE,
rownames=FALSE
)
return(dataDT)
})
output$geneTable <- DT::renderDT({
marker.tab <- getGeneTable()
if(nrow(marker.tab) > 0){
marker.tab <- marker.tab[,c(10,8,9,3,11:ncol(marker.tab))]
}
dataDT <- DT::datatable(marker.tab,
## colnames=c('Ensembl ID','Symbol','Entrez ID','Gene Type','CM tissueType','CM cancerType','CM cellType','CM cellName','Unique','cluster p-val','cluster fc','cluster-all fc'),
selection='single',
options=list(
'searching'=TRUE,
'legnthChange'=FALSE,
'pagingType'='full',
'autoWidth'=TRUE,
'pageLength'=25),
escape=FALSE,
rownames=FALSE
)
return(dataDT)
})
output$sampleTable <- DT::renderDT({
dataDT <- DT::datatable(getSampleTable()[,c(-6)],
options = list(pageLength=25
),
escape=FALSE
)
return(dataDT)
})
output$selectionList <- DT::renderDT({
datalist <- selection.getDatalist()
dataDT <- DT::datatable(datalist,
options = list(
searching = FALSE,
paging = FALSE,
info = FALSE)
)
return(dataDT)
})
observeEvent(input$topNavBar, {
if(input$topNavBar == 'violinPanel'){user.selections$violinGroupRendered <- TRUE}
if(input$topNavBar == 'genePanel' | input$topNavBar == 'samplePanel' | input$topNavBar == 'wgcnaPanel'){
runjs(" var $this = $('#controlPanelClickable');
if(!$this.hasClass('panel-collapsed')) {
$this.parents('.panel').find('.panel-body').slideUp();
$this.addClass('panel-collapsed');
$this.find('i').removeClass('glyphicon-chevron-up').addClass('glyphicon-chevron-down');
}")
}
else if(user.selections$previous.tab == 'genePanel' | user.selections$previous.tab == 'samplePanel' | user.selections$previous.tab == 'wgcnaPanel'){
runjs(" var $this = $('#controlPanelClickable');
if($this.hasClass('panel-collapsed')) {
$this.parents('.panel').find('.panel-body').slideDown();
$this.removeClass('panel-collapsed');
$this.find('i').removeClass('glyphicon-chevron-down').addClass('glyphicon-chevron-up');
}")
}
user.selections$previous.tab = input$topNavBar
})
observeEvent(input$gene.vec, {
getDistance <- function(x,gene.vec) {
## eu.dist <- sum((x - gene.vec)^2)
eu.dist <- cor(x,gene.vec[1,],method='pearson')
## eu.dist <- cor(x,gene.vec,method='spearman')
## eu.dist <- (x %*% gene.vec) / (norm(x,'2') * norm(gene.vec,'2'))
return(eu.dist)
}
progress <- shiny::Progress$new()
on.exit(progress$close())
progress$set(message='Calculating...', value=0.33)
## map.dat <- readRDS('data/recount_750_dim_noProj_over50_pc3sd_poscounts.RDS')
## rotation.dat <- readRDS('data/recount_all_big_irlba_750_over50_pc3sd_poscounts_rotmat.RDS')
## map.centers <- readRDS('data/recount_over50_bulkOnly_pc3sd_poscounts_colparams.RDS')
## gene.means <- readRDS('data/recount_over50_pc3sd_geoMeansNZ.RDS')
## map.dat <- readRDS('data/recount_750_dim_noProj_over50_pc3sd_tpm_log.RDS')
## rotation.dat <- readRDS('data/recount_all_big_irlba_750_over50_pc3sd_tpm_log_rotmat.RDS')
## map.centers <- readRDS('data/recount_over50_pc3sd_colparams_tpm_log.RDS')
map.dat <- readRDS('data/recount_100_dim_noProj_over50_pc3sd_tpm_log_90th_var_genes.RDS')
rotation.dat <- readRDS('data/recount_all_big_irlba_100_over50_pc3sd_tpm_log_90th_var_genes_rotmat.RDS')
map.centers <- readRDS('data/recount_over50_pc3sd_colparams_tpm_log_90th_var_genes.RDS')
gene.lens <- read.table('data/ensembl_gene_lengths.tsv',sep='\t',stringsAsFactors=F,row.names=1)
map.centers <- subset(map.centers,vars>0)
gene.lens <- gene.lens[rownames(map.centers),]
gene.dat <- read.table(input$gene.vec$datapath,sep='\t',header=T)
gene.dat <- gene.dat[rownames(map.centers),,drop=F]
input.names <- colnames(gene.dat)
gene.dat <- gene.dat / gene.lens
normFactors <- colSums(gene.dat)
gene.dat <- 1e6 * data.matrix(gene.dat) %*% diag(1/normFactors,nrow=length(normFactors))
gene.dat <- log(gene.dat+1)
colnames(gene.dat) <- input.names
dist.mat <- matrix(0,nrow=nrow(map.dat),ncol=ncol(gene.dat))
rownames(dist.mat) <- rownames(map.dat)
colnames(dist.mat) <- colnames(gene.dat)
for(col in colnames(gene.dat)){
## gene.vec <- gene.dat[[col]]
gene.vec <- gene.dat[,col,drop=F]
names(gene.vec) <- rownames(gene.dat)
## gene.ratios <- gene.vec / gene.means
## size.factor <- median(gene.ratios[is.finite(gene.ratios) & gene.ratios > 0])
## gene.vec <- gene.vec / size.factor
center.vec <- gene.vec - map.centers$means
center.vec <- center.vec / map.centers$vars
rot.vec <- t(center.vec) %*% rotation.dat
dist.vec <- apply(map.dat,1,getDistance,gene.vec=rot.vec)
dist.mat[,col] <- dist.vec
}
progress$set(message='Calculated', value=0.67)
dat.rows <- rownames(data())
dist.mat <- dist.mat[dat.rows,,drop=F]
for(col in colnames(dist.mat)){
dist.vec <- dist.mat[,col]
names(dist.vec) <- rownames(dist.mat)
user.selections$gene.input.results[[length(user.selections$gene.input.results)+1]] <- dist.vec
## user.selections$gene.input.datalist <- rbind(user.selections$gene.input.datalist,data.frame('name'=col,'min'=min(log2(dist.vec+1))))
user.selections$gene.input.datalist <- rbind(user.selections$gene.input.datalist,data.frame('name'=col,'max'=max(dist.vec)))
}
progress$set(message='Read results',value=1)
})
data <- reactive({
tsne.y <- data.frame(tsne.data)
colnames(tsne.y) <- c('y1','y2')
tsne.y <- cbind(tsne.y,tsne.meta)
return(tsne.y)
})
geneVec <- reactive({
## geneVec <- NULL
if(input$whichGene == ''){
## if(TRUE){
return(NULL)
}
## gene.id <- strsplit(input$whichGene,', ')[[1]][3]
gene.id <- input$whichGene
gene.req <- dbSendQuery(con,sprintf("SELECT vals FROM gene_vals WHERE gene_id = '%s'",gene.id))
gene.info <- fromJSON(dbFetch(gene.req)[1,1])
dbClearResult(gene.req)
## gene.info <- fromJSON(sprintf('http://localhost:3000/gene_vals/%s',gene.id))
names(gene.info) <- gene.tpm.samps
print(head(gene.info))
geneVec <- rep(NA,length(tsne.order))
names(geneVec) <- tsne.order
names.used <- intersect(tsne.order,gene.tpm.samps)
geneVec[names.used] <- gene.info[names.used]
## if(input$geneScale == 'log2gene'){
## geneVec <- log2(geneVec)
## } else if(input$geneScale == 'log2gene1'){
## geneVec <- log2(geneVec + 1)
## }
## gene.info <- gene.info[tsne.order]
## return(geneVec)
return(geneVec)
})
tissueVec <- reactive({
tree <- input$tissueTree
if(is.null(tree) | length(get_selected(tree)) == 0){
colVar <- NULL
} else{
tissue.selection <- unlist(get_selected(tree))
tissue.id <- strsplit(tissue.selection,':')[[1]][1]
tiss.req <- dbSendQuery(con,sprintf("SELECT termtree FROM tissue_tree WHERE id = '%s'",tissue.id))
tissue.info <- fromJSON(dbFetch(tiss.req)$termtree)
dbClearResult(tiss.req)
## tissue.info <- fromJSON(sprintf('http://localhost:3000/tissue_info/%s',tissue.id))
## tissue.req <- dbFetch(dbSendQuery(mercator.db.con,sprintf("SELECT termtree FROM tissue_tree WHERE id='%s'",tissue.id)))
## tissue.info <- fromJSON(tissue.req$termtree)
colVar <- rep('unlabelled',length(tsne.order))
names(colVar) <- tsne.order
for(label in names(tissue.info)){
used.ids <- intersect(tsne.order,tissue.info[[label]])
colVar[used.ids] <- label
}
}
return(colVar)
})
doidVec <- reactive({
tree <- input$doidTree
if(is.null(tree) | length(get_selected(tree)) == 0){
colVar <- NULL
} else{
doid.selection <- unlist(get_selected(tree))
doid.split <- strsplit(doid.selection,':')[[1]]
doid.id <- paste(doid.split[1],doid.split[2],sep='_')
doid.req <- dbSendQuery(con,sprintf("SELECT termtree FROM doid_dat WHERE id = '%s'",doid.id))
doid.info <- fromJSON(dbFetch(doid.req)$termtree)
dbClearResult(doid.req)
## doid.info <- fromJSON(sprintf('http://localhost:3000/doid_info/%s',doid.id))
## doid.info <- fromJSON(doid.req$termtree)
colVar <- rep('unlabelled',length(tsne.order))
names(colVar) <- tsne.order
for(label in names(doid.info)){
used.ids <- intersect(tsne.order,doid.info[[label]])
colVar[used.ids] <- label
}
}
return(colVar)
})
efoVec <- reactive({
tree <- input$efoTree
if(is.null(tree) | length(get_selected(tree)) == 0){
colVar <- NULL
} else{
efo.selection <- unlist(get_selected(tree))
efo.split <- strsplit(efo.selection,':')[[1]]
efo.id <- paste(efo.split[1],efo.split[2],sep='_')
efo.req <- dbSendQuery(con,sprintf("SELECT termtree FROM efo_tree WHERE id = '%s'",efo.id))
efo.info <- fromJSON(dbFetch(efo.req)$termtree)
dbClearResult(efo.req)
## efo.info <- fromJSON(sprintf('http://localhost:3000/efo_info/%s',efo.id))
colVar <- rep('unlabelled',length(tsne.order))
names(colVar) <- tsne.order
for(label in names(efo.info)){
used.ids <- intersect(tsne.order,efo.info[[label]])
colVar[used.ids] <- label
}
}
return(colVar)
})
meshVec <- reactive({
tree <- input$meshTree
if(is.null(tree) | length(get_selected(tree)) == 0){
colVar=NULL
} else{
mesh.selection <- unlist(get_selected(tree))
mesh.id <- strsplit(mesh.selection,':')[[1]][1]
mesh.req <- dbSendQuery(con,sprintf("SELECT termtree FROM mesh_tree WHERE id = '%s'",mesh.id))
mesh.info <- fromJSON(dbFetch(mesh.req)$termtree)
dbClearResult(mesh.req)
## mesh.info <- fromJSON(sprintf('http://localhost:3000/ontology_info/%s',mesh.id))
## mesh.req <- dbFetch(dbSendQuery(mercator.db.con,sprintf("SELECT termtree FROM mesh_tree WHERE id='%s'",mesh.id)))
## mesh.info <- fromJSON(mesh.req$termtree)
colVar <- rep('unlabelled',length(tsne.order))
names(colVar) <- tsne.order
for(label in names(mesh.info)){
used.ids <- intersect(tsne.order,mesh.info[[label]])
colVar[used.ids] <- label
}
}
return(colVar)
})
selectionVec <- reactive({
## rows <- input$selectionList_rows_selected
## if(is.null(rows)){
## return(NULL)
## }
if(length(user.selections$selection.list) == 0){
return(NULL)
}
## indVec <- c()
## groupVec <- c()
## dataResults <- data()
results <- data.frame()
## for(rowNum in rows){
for(rowNum in 1:length(user.selections$selection.list)){
entry <- user.selections$selection.list[[rowNum]]
rowLabel <- sprintf('Selection: %s',user.selections$selection.datalist[rowNum,'name'])
results <- rbind(results,data.frame(samps=entry,group=rep(rowLabel,length(entry)),stringsAsFactors=F))
}
return(results)
})
projectionVec <- reactive({
rows <- input$sampleInputTable_rows_selected
if(is.null(rows)){
return(NULL)
}
entry <- user.selections$gene.input.results[[rows]]
return(entry)
})
selectionBarVec <- reactive({
rows <- input$selectionList_rows_selected
if(is.null(rows) & length(user.selections$selection.list) > 0){
rows <- 1:length(user.selections$selection.list)
}
indVec <- c()
groupVec <- c()
dataResults <- data()
results <- data.frame()
for(rowNum in rows){
entry <- user.selections$selection.list[[rowNum]]
rowLabel <- sprintf('Selection: %s',user.selections$selection.datalist[rowNum,'name'])
results <- rbind(results,data.frame(samps=entry,group=rep(rowLabel,length(entry))))
}
return(results)
})
violinColVar <- reactive({
colVar <- NULL
if(input$colorButton == 0 | input$violinXFactors %in% c('No Coloring','Gene','Mesh','Tissue','DOID','efo','KMeans','Louvain','Projection')){
return(colVar)
}
colVar = apply(data()[,input$violinXFactors,drop=FALSE],1,paste,collapse='+')
return(colVar)
})
kmeansVec <- reactive({
## print(input$kmeansChoice)
return(kmeans.dat[[as.numeric(input$kmeansChoice)]])
})
louvainVec <- reactive({
return(louvain.vec)
})
colVar <- reactive({
colVar <- NULL
## if(TRUE){return(colVar)}
if(input$colorButton == 0 | input$colorfactors %in% c('No Coloring','Gene','Mesh','Tissue','DOID','efo','KMeans','Louvain','Projection')){
return(colVar)
}
colVar = apply(data()[,input$colorfactors,drop=FALSE],1,paste,collapse='+')
## }
return(colVar)
## }
})
barColVar <- reactive({
colVar <- NULL
## if(TRUE){return(colVar)}
if(input$colorButton == 0 | input$barPlotXaxis %in% c('No Coloring','Gene','Mesh','Tissue','DOID','efo','KMeans','Louvain','Projection','marker_tissue_type','marker_cancer_type','marker_cell_type','marker_cell_name')){
return(colVar)
}
colVar = apply(data()[,input$barPlotXaxis,drop=FALSE],1,paste,collapse='+')
return(colVar)
})
output$plotlyClick <- renderUI({
resp <- try({
click.event <- event_data('plotly_click',source='tsne')
if(is.null(click.event) == T) return('Click on a t-SNE point to link to SRA entry')
curveNumber <- click.event$curveNumber+1
inds <- click.event$pointNumber+1
run.id <- user.selections$tsne.traces[[curveNumber]][inds]
samp.id <- tsne.meta[run.id,'samp_id']
case.id <- tsne.meta[run.id,'gdc_cases.case_id']
if(is.na(run.id)) return('Click on a t-SNE point to link to SRA entry')
if(tsne.meta[run.id,'proj_id'] == 'TCGA'){
url <- a(sprintf('Link to TCGA case %s',samp.id),href=sprintf('https://portal.gdc.cancer.gov/cases/%s',case.id),target='_blank')
} else{
url <- a(sprintf('Link to SRA run %s',user.selections$tsne.traces[[curveNumber]][inds]),href=sprintf('https://trace.ncbi.nlm.nih.gov/Traces/sra/?run=%s',user.selections$tsne.traces[[curveNumber]][inds]),target='_blank')
}
return(tagList(url))
})
return(resp)
})
getWgcnaGoTable <- reactive({
go.tab <- wgcna.dat[['cats']][[input$wgcnaTabControl]]
colnames(go.tab) <- c('Category','Term','Ontology','p-val')
return(go.tab)
})
getWgcnaGeneTable <- reactive({
gene.tab <- wgcna.dat[['genes']][[input$wgcnaTabControl]]
colnames(gene.tab) <- c('Symbol','ID','Ensembl','Gene Type','CM tissueType','CM cancerType','CM cellType','CM cellName','Gene Symbol','Entrez ID','Ensembl ID')
return(gene.tab)
## return(gene.tab[,c(11,9,10,4,5,6,7,8)])
})
getGeneTable <- reactive({
if(input$geneGroupSecond == 'all'){
label.1 <- 'all'
label.2 <- input$geneGroup
label <- sprintf('%s.%s',label.1,label.2)
marker.req <- dbSendQuery(con,sprintf("SELECT gene_table FROM pairwise_markers WHERE pair_id = '%s'",label))
marker.tab <- fromJSON(dbFetch(marker.req)$gene_table)
dbClearResult(marker.req)
## marker.tab <- fromJSON(sprintf('http://localhost:3000/pairwise_markers/%s',label))
rownames(marker.tab) <- marker.tab[,1]
colnames(marker.tab) <- c('ens_id','unique','p-val','unique-fcs','total-fcs','stat')
marker.tab <- cbind(cellmarker.info[rownames(marker.tab),],marker.tab[,c(2,3,4,5,6)],stringsAsFactors=F)
marker.tab <- marker.tab[,c(-3)]
colnames(marker.tab) <- c('Symbol','ID','Gene Type','CM tissueType','CM cancerType','CM cellType','CM cellName','Gene Symbol','Entrez ID','Ensembl ID','unique','p-val','unique-fcs','total-fcs','stat')
marker.tab[['unique-fcs']] <- as.numeric(marker.tab[['unique-fcs']])
marker.tab[['total-fcs']] <- as.numeric(marker.tab[['total-fcs']])
## marker.tab <- marker.tab[order(marker.tab[['unique-fcs']],decreasing=T),]
}
else if(input$geneGroup == input$geneGroupSecond){
return(subset(data.frame('name'=c(1,2),'min'=c(2,3)),name>3)) ## TODO modify to have all columns
}
else{
label.1 <- as.numeric(input$geneGroup)
label.2 <- as.numeric(input$geneGroupSecond)
mult <- -1
if(label.1 > label.2){
tmp <- label.1
label.1 <- label.2
label.2 <- tmp
mult <- 1
}
label <- sprintf('%s.%s',label.1,label.2)
marker.req <- dbSendQuery(con,sprintf("SELECT gene_table FROM pairwise_markers WHERE pair_id = '%s'",label))
marker.tab <- fromJSON(dbFetch(marker.req)$gene_table)
dbClearResult(marker.req)
## marker.tab <- fromJSON(sprintf('http://localhost:3000/pairwise_markers/%s',label))
rownames(marker.tab) <- marker.tab[,1]
colnames(marker.tab) <- c('ens_id','p-val','fc','test.stat')
## colnames(marker.tab) <- c('ens_id','p-val','fc','test.stat','wilcox')
## marker.tab <- cbind(cellmarker.info[rownames(marker.tab),],marker.tab[,c(2,3,4,5)],stringsAsFactors=F)
marker.tab <- cbind(cellmarker.info[rownames(marker.tab),],marker.tab[,c(2,3,4)],stringsAsFactors=F)
marker.tab <- marker.tab[,c(-3)]
## colnames(marker.tab) <- c('Symbol','ID','Gene Type','CM tissueType','CM cancerType','CM cellType','CM cellName','Gene Symbol','Entrez ID','Ensembl ID','p-val','log2fc','test.stat','scaled wilcox stat')
colnames(marker.tab) <- c('Symbol','ID','Gene Type','CM tissueType','CM cancerType','CM cellType','CM cellName','Gene Symbol','Entrez ID','Ensembl ID','p-val','log2fc','test.stat')
marker.tab[['log2fc']] <- as.numeric(marker.tab[['log2fc']])*mult
marker.tab[['test.stat']] <- as.numeric(marker.tab[['test.stat']])*mult
marker.tab <- marker.tab[order(marker.tab$test.stat,decreasing=T),]
}
## label.2 <- as.numeric(input$geneGroupSecond)+1
## label <- sprintf('%s.%s',label.1,label.2)
## marker.tab <- fromJSON(sprintf('http://localhost:3000/pairwise_markers/%s',label))
## rownames(marker.tab) <- marker.tab[,1]
## colnames(marker.tab) <- c('ens_id','p-val','unique-fcs','total-fcs')
## marker.tab <- cbind(cellmarker.info[rownames(marker.tab),],marker.tab[,c(2,3,4)],stringsAsFactors=F)
## marker.tab <- marker.tab[,c(-3)]
## colnames(marker.tab) <- c('Symbol','ID','gene-type','tissueType','cancerType','cellType','cellName','p-val','unique-fcs','total-fcs')
marker.tab[['p-val']] <- as.numeric(marker.tab[['p-val']])
return(marker.tab)
## if(input$geneGroup == 'all'){
## dt <- marker.list[['all']]
## } else{
## dt <- marker.list[[as.double(input$geneGroup)+1]]
## }
})
getSampleTable <- reactive({
selectionRes <- selectionVec()
louvainVec <- louvainVec()
meshResults <- meshVec()
tissueResults <- tissueVec()
doidResults <- doidVec()
efoResults <- efoVec()
dt <- tsne.meta[,c(1,2,3,4,6,7,8,9)]
colnames(dt) <- c('proj_id','samp_id','run_id','sample_type','url','tcga_case_id','tissue_general','tissue_detail')
dt$Louvain <- louvainVec
if(is.null(meshResults)){
dt$mesh <- NA
} else{
dt$mesh <- meshResults
}
if(is.null(tissueResults)){
dt$tissue <- NA
} else{
dt$tissue <- tissueResults
}
if(is.null(doidResults)){
dt$doid <- NA
} else{
dt$doid <- doidResults
}
if(is.null(efoResults)){
dt$efo <- NA
} else{
dt$efo <- efoResults
}