marcelcosta
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BDAccess
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Merge branch 'dev'

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marcelcosta 2 years ago
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38e902cef0 cb6c739d14
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1 changed files with 246 additions and 7 deletions
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      BDAccess/app.R

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BDAccess/app.R
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@ -5,6 +5,13 @@ library(reshape2)
library(Matrix)
library(CitFuns)
library(BDCIT)
library(openCyto)
library(flowCore)
library(flowWorkspace)
library(CytoML)
library(ggcyto)
filter<-dplyr::filter
print(getwd())
source("../sqlFunctions.R", encoding = "UTF-8")
@ -19,6 +26,8 @@ rna<-data.frame("UMID"="","UM"="")
sqlInitialize(ruta="../ruta_database.R")
# UI ----
ui <- fluidPage(
# Application title
@ -27,6 +36,8 @@ ui <- fluidPage(
#sidebarLayout(
#Navbar
navbarPage("BDAccess",
## Update ----
tabPanel("Update",
sidebarPanel(
selectInput("dbtype", "", selected="UM", choices=c("UM", "OV","CC")),
@ -52,6 +63,8 @@ ui <- fluidPage(
)
)
),
## Visor ----
tabPanel("Visor",
sidebarPanel(
radioButtons("nhc", label = h3("Código"),
@ -63,9 +76,35 @@ ui <- fluidPage(
mainPanel(
htmlOutput("report"),
h3("Nitrogen"),
tableOutput("nitrogen")
tableOutput("nitrogen"),
plotOutput("visorplot", height = "1000px")
)
),
## Citometría ----
tabPanel("Citometría",
sidebarPanel(
selectInput("phenotype", "Tipo de análisis", selected="Pop", choices=c("Pop", "IC")),
),
mainPanel(
tabsetPanel(
tabPanel("Entrada",
actionButton("goButtonDir","Selecciona directorio fenotipo"),
textOutput("session"),
hr(),
actionButton("fcsconvert", "Convertir a fcs"),
hr(),
actionButton("pngexport", "Exportar informes"),
actionButton("popexport", "Actualizar BBDD")
),
tabPanel("Visor",
)
)
)
),
## scRNAseq ----
tabPanel("scRNAseq",
sidebarPanel(
textInput("sqlquery", label = "sqlquery", value = ""),
@ -87,10 +126,11 @@ ui <- fluidPage(
)
# Define server logic required to draw a histogram
# Server ----
server <- function(input, output) {
## Update
## Update ----
values <- reactiveValues()
values[["DF"]]<-DF
values[["samples"]]<-samples
@ -618,8 +658,9 @@ server <- function(input, output) {
}
})
## Visor
## Visor ----
output$report<-renderUI({
samples<-sqlFetch(dta, "samples")
if (input$nhc == 1){samples_sel<-samples %>% filter(OVID == input$id)}
@ -786,8 +827,206 @@ server <- function(input, output) {
})
## scRNAseq
output$visorplot<-renderPlot({
if (input$nhc == 3){
pops<-sqlFetch(dta, "POPULATIONS")
g_pop<-pops %>% dplyr::filter(samples == input$id) %>% gather(pop,value,-samples) %>%
mutate(pop=factor(pop, levels=c("CD45pos_Alive","T_cells","CD8","CD4","DN","NK", "B_cells",
"CD45neg_LDneg","EpCAMneg_HLAIneg","EpCAMneg_HLAIpos","EpCAMpos_HLAIpos"))) %>%
ggplot(aes(pop, value))+
geom_bar(stat="identity", color="black", fill="grey70")+
labs(title = input$id, y="% parent", x="")+
theme_bw()+
theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5))
tl<-sqlFetch(dta, "IC") %>% filter(samples == input$id)
mtl<-melt(tl, variable.name = "Receptors")
mtl$Receptors<-as.character(mtl$Receptors) #Para poder depurar bien el texto, lo pasamos a tipo character
mtl$Receptors<-gsub("n","-",mtl$Receptors, fixed = T)
mtl$Receptors<-gsub("p","+",mtl$Receptors, fixed = T)
mtl$Receptors<-gsub("_"," ",mtl$Receptors)
mtl[mtl$value < 1, "Receptors"]<-"Other"
mtl$Receptors<-gsub("[A-Z]*-*[0-9T]- *", "", mtl$Receptors)
mtl$Receptors<-gsub("+ $", "", mtl$Receptors)
mtl$Receptors[mtl$Receptors == ""]<-"All Negative"
mtl$Receptors<-factor(mtl$Receptors)
mtl$Population<-factor(mtl$Population, levels = c("CD8", "CD4"))
# colorCount<-length(unique(mtl$Receptors))
# getPalette = colorRampPalette(RColorBrewer::brewer.pal(12, "Set3"))
color<-c(c("CTLA4+ LAG3+ PD1+ TIGIT+ TIM3+"="black","All Negative"="white","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E","TIGIT+"="#FA7055"),
c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F","PD1+ TIGIT+"="#D259AA", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "CTLA4+ TIGIT+"="#9C929A", "LAG3+ TIM3+"="#9ED848", "TIGIT+ TIM3+"="#ACB353", "LAG3+ TIGIT+"="#EC964A"),
c("CTLA4+ PD1+ TIGIT+"="#B86B6A","CTLA4+ PD1+ TIGIT+ TIM3+"="#B81515","LAG3+ PD1+ TIGIT+"="#007D8A", "PD1+ TIGIT+ TIM3+"="#D64545", "LAG3+ PD1+ TIGIT+ TIM3+"="#0f5860", "LAG3+ TIGIT+ TIM3+"="#50cad3"))
g_IC<-ggplot(mtl, aes(samples, value, fill=Receptors))+
geom_bar(stat="summary", fun="sum",color="black")+
labs(x="Patient", y="% CD8+", fill="")+
facet_grid(.~Population)+
scale_fill_manual(values = color[levels(mtl$Receptors)[levels(mtl$Receptors) %in% unique(mtl$Receptors)]])+
theme_bw()+
theme(axis.text.x=element_text(angle=45, hjust=1))
ggpubr::ggarrange(g_pop, g_IC, heights = c(0.4, 0.6), ncol = 1)
}
})
## Citometría ----
observe({
if(input$goButtonDir > 0){
cito_dir<<-choose.dir() %>% gsub("\\","/",. ,fixed=T) %>% paste0("/")
output$session <- renderText(
cito_dir
)
}
})
observeEvent(input$fcsconvert,{
route<-cito_dir
files<-list.files(route, ".LMD")
for (lmd in files){
fcs<-read.FCS(paste0(route,lmd), dataset = 2)
# fcs@parameters$desc<-c("FS-A","SS-A", paste("FL",1:10,"-A", sep = ""), "TIME")
# fcs@parameters$desc<-c("FS-H","FS-A","FS-W","SS-H","SS-A","TIME", paste("FL",1:10,"-A", sep = ""))
keyword(fcs)['$FIL']<-paste0(gsub(".LMD","",lmd), ".fcs")
write.FCS(fcs, paste0(route, gsub(".LMD","",lmd), ".fcs"))
}
})
observeEvent(input$pngexport,{
if (input$phenotype == "Pop"){
route<-cito_dir
ws<-open_flowjo_xml(paste0(route,"Populations.wsp"))
gs<-flowjo_to_gatingset(ws, name="All Samples")
sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Pop ")[[1]][2]) %>%
gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
for (samp in sampleNames(gs)){
print(samp)
p<-autoplot(gs[[samp]], bins=64)
ggsave(paste0(route, samp,".pop.png"),p,width = 10, height = 10)
}
}
if (input$phenotype == "IC"){
route<-cito_dir
ws<-open_flowjo_xml(paste0(route,"IC.wsp"))
gs<-flowjo_to_gatingset(ws, name="All Samples")
sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "ICs ")[[1]][2]) %>%
gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
names<-sampleNames(gs) %>% gsub("ab|Ab|AB|iso|Iso|ISO| ","",.) %>% unique()
nodes<-gs_get_pop_paths(gs)
nodes_parent<-nodes[!grepl("CTLA4|LAG3|PD1|TIGIT|TIM3|root$", nodes)]
nodes_cd4<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIGIT$|TIM3$", nodes) & grepl("/CD4/",nodes)]
nodes_cd8<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIGIT$|TIM3$", nodes) & grepl("/CD8/",nodes)]
for (id in names){
print(id)
iso<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("iso",sampleNames(gs))]
ab<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("ab",sampleNames(gs))]
g1<-ggcyto_arrange(autoplot(gs[[ab]], nodes_parent, bins=128), nrow=1)
g2<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd8, bins=64), nrow=1)
g3<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd8, bins=64), nrow=1)
g4<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd4, bins=64), nrow=1)
g5<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd4, bins=64), nrow=1)
g_all<-gridExtra::gtable_rbind(g1,g2,g3,g4,g5)
ggsave(paste0(route,id,".IC.png"), g_all, width = 10, height = 10)
}
}
})
observeEvent(input$popexport,{
if (input$phenotype == "Pop"){
route<-cito_dir
ws<-open_flowjo_xml(paste0(route,"Populations.wsp"))
gs<-flowjo_to_gatingset(ws, name="All Samples")
sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Pop ")[[1]][2]) %>%
gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
nodes<-sapply(strsplit(gs_get_pop_paths(gs), "/"), tail, 1)
nodes<-nodes[grepl("_",nodes)]
pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
pop[,"pop"]<-gsub("_","",pop$pop)
pop$pop<-gsub(" ","_",pop$pop)
pop$pop<-gsub("+","pos",pop$pop, fixed=T)
pop$pop<-gsub("-","neg",pop$pop, fixed=T)
pop<-rename(pop, "samples"="sample")
pop$percent<-round(pop$percent, digits=2)
pop_sp<-pop %>% spread(pop, percent)
pop_sql<-sqlFetch(dta, "POPULATIONS") %>% slice(0)
pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql))
vartypes<-rep("Number", pop_sp %>% select(-samples) %>% colnames %>% length)
names(vartypes)<-pop_sp %>% select(-samples) %>% colnames
sqlSave(dta, pop_sp, tablename="POPULATIONS", append = T, varTypes = vartypes, rownames = F)
print("Tabla POPULATIONS sincronizada.")
}
if (input$phenotype == "IC"){
route<-cito_dir
ws<-open_flowjo_xml(paste0(route,"IC.wsp"))
gs<-flowjo_to_gatingset(ws, name="All Samples")
sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "ICs ")[[1]][2]) %>%
gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
nodes<-gs_get_pop_paths(gs)
# nodes<-gsub("â\u0081»", "-", nodes)
# nodes<-gsub("â\u0081º", "+", nodes)
nodes<-nodes[grepl("CTLA4", nodes)]
nodes<-nodes[!grepl("CD4$|CD8$|CTLA4$|TIM3$|PD1$|LAG3$|TIGIT$|/CTLA4â\u0081»$|/TIM3â\u0081»$|/PD1â\u0081»$|/LAG3â\u0081»$|/TIGITâ\u0081»$", nodes)]
pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
pop$percent<-round(pop$percent, digits=2)
pop$pop<-gsub("â\u0081»", "n", pop$pop)
pop$pop<-gsub("â\u0081º", "p", pop$pop)
pop$pop<-gsub(" ", "_", pop$pop)
pop["Type"]<-"ab"
pop[grepl("iso|ISO|Iso",pop$sample),"Type"]<-"iso"
pop$sample<-gsub("iso|ISO|Iso|ab|AB|Ab| ","",pop$sample)
pop_sp<-pop %>% spread(Type, percent)
pop_sp["Net"]<-pop_sp$ab
pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"Net"]<-pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"ab"]-pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"iso"]
pop_sp$Net[pop_sp$Net < 0]<-0
pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/","",.)
pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net)
pop_sp$`CTLA4n_LAG3n_PD1n_TIGITn_TIM3n`<- pop_sp %>% select(-`CTLA4n_LAG3n_PD1n_TIGITn_TIM3n`) %>% group_by(sample,Population) %>%
gather(pop, value, -sample,-Population) %>% summarise(n=100-sum(value)) %>% pull(n)
pop_sp <- rename(pop_sp, "samples"="sample")
vartypes<-rep("Number", pop_sp %>% select(-samples, -Population) %>% colnames %>% length)
names(vartypes)<-pop_sp %>% select(-samples, -Population) %>% colnames
sqlSave(dta, pop_sp, tablename="IC", append = T, varTypes = vartypes, rownames = F)
print("Tabla IC sincronizada.")
}
})
## scRNAseq ----
output$PATID = renderUI({
observeEvent(input$goButton, {})
sc_cod<-sqlFetch(dta, "CNAG") %>% pull(CODIGO)

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