Gates booleanas se hacen en R y no en Flowjo (que enlentece mucho el análisis).

BDAccess/app.R

@@ -1079,17 +1079,47 @@ server <- function(input, output) {
             sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "ICs ")[[1]][2]) %>% 
                 gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
             
+            bool.comb<-apply(
+                expand.grid(c("","!"), c("","!"),c("","!"), c("","!"), c("","!")),
+                1,
+                function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIGIT & ",x[5], "TIM3")
+            )
+            
+            bool.name<-apply(
+                expand.grid(c("+","-"), c("+","-"),c("+","-"), c("+","-"), c("+","-")),
+                1,
+                function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIGIT",x[4]," TIM3",x[5])
+            )
+            
+            for (i in 1:length(bool.comb)){
+                print("Booleanos CD8")
+                call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
+                boolgate<-eval(call)
+                gs_pop_add(gs, boolgate, parent="CD8", name = bool.name[i])
+            }
+            
+            for (i in 1:length(bool.comb)){
+                print("Booleanos CD4")
+                call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
+                boolgate<-eval(call)
+                gs_pop_add(gs, boolgate, parent="CD4", name = bool.name[i])
+            }
+            
+            recompute(gs)
+            
             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)]
+            nodes<-nodes[!grepl("CD4$|CD8$|CTLA4$|TIM3$|PD1$|LAG3$|TIGIT$", 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$pop<-gsub("â\u0081»", "n", pop$pop)
+            # pop$pop<-gsub("â\u0081º", "p", pop$pop)
+            pop$pop<-gsub("-", "n", pop$pop, fixed=T)
+            pop$pop<-gsub("+", "p", pop$pop, fixed=T)
             pop$pop<-gsub(" ", "_", pop$pop)
             
             pop["Type"]<-"ab"
@@ -1104,10 +1134,13 @@ server <- function(input, output) {
             pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
             
             pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net)
-            pop_sp$`CTLA4n_LAG3n_PD1n_TIGITn_TIM3n`<- pop_sp %>% select(-`CTLA4n_LAG3n_PD1n_TIGITn_TIM3n`) %>% group_by(sample,Population) %>% 
+            pop_sp$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")
             
+            pop_sql<-sqlFetch(dta, "IC") %>% slice(0)
+            pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql))
+            
             vartypes<-rep("Number", pop_sp %>% select(-samples, -Population) %>% colnames %>% length)
             names(vartypes)<-pop_sp %>% select(-samples, -Population) %>% colnames