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@ -1016,25 +1016,173 @@ server <- function(input, output) { |
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sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "ICs ")[[1]][2]) %>% |
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gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T) |
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bool.comb<-apply( |
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expand.grid(c("","!"), c("","!"),c("","!"), c("","!"), c("","!")), |
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1, |
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function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIGIT & ",x[5], "TIM3") |
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) |
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bool.name<-apply( |
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expand.grid(c("+","-"), c("+","-"),c("+","-"), c("+","-"), c("+","-")), |
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1, |
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function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIGIT",x[4]," TIM3",x[5]) |
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) |
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print("Booleanos CD8") |
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for (i in 1:length(bool.comb)){ |
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call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i]))) |
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boolgate<-eval(call) |
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gs_pop_add(gs, boolgate, parent="CD8", name = bool.name[i]) |
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} |
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print("Booleanos CD4") |
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for (i in 1:length(bool.comb)){ |
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call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i]))) |
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boolgate<-eval(call) |
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gs_pop_add(gs, boolgate, parent="CD4", name = bool.name[i]) |
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} |
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recompute(gs) |
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names<-sampleNames(gs) %>% gsub("ab|Ab|AB|iso|Iso|ISO| ","",.) %>% unique() |
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nodes<-gs_get_pop_paths(gs) |
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nodes_parent<-nodes[!grepl("CTLA4|LAG3|PD1|TIGIT|TIM3|root$", nodes)] |
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nodes_cd4<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIGIT$|TIM3$", nodes) & grepl("/CD4/",nodes)] |
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nodes_cd8<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIGIT$|TIM3$", nodes) & grepl("/CD8/",nodes)] |
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# nodes<-gsub("â\u0081»", "-", nodes) |
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# nodes<-gsub("â\u0081º", "+", nodes) |
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nodes<-nodes[grepl("CTLA4", nodes)] |
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nodes<-nodes[!grepl("CD4$|CD8$|CTLA4$|TIM3$|PD1$|LAG3$|TIGIT$", nodes)] |
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pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100) |
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pop$percent<-round(pop$percent, digits=2) |
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# pop$pop<-gsub("â\u0081»", "n", pop$pop) |
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# pop$pop<-gsub("â\u0081º", "p", pop$pop) |
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pop$pop<-gsub("-", "n", pop$pop, fixed=T) |
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pop$pop<-gsub("+", "p", pop$pop, fixed=T) |
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pop$pop<-gsub(" ", "_", pop$pop) |
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pop["Type"]<-"ab" |
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pop[grepl("iso|ISO|Iso",pop$sample),"Type"]<-"iso" |
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pop$sample<-gsub("iso|ISO|Iso|ab|AB|Ab| ","",pop$sample) |
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pop_sp<-pop %>% spread(Type, percent) |
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pop_sp["Net"]<-pop_sp$ab |
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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$pop),"iso"] |
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pop_sp$Net[pop_sp$Net < 0]<-0 |
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pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/","",.) |
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pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1) |
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pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net) |
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pop_sp$CTLA4n_LAG3n_PD1n_TIGITn_TIM3n<- pop_sp %>% select(-CTLA4n_LAG3n_PD1n_TIGITn_TIM3n) %>% group_by(sample,Population) %>% |
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gather(pop, value, -sample,-Population) %>% summarise(n=100-sum(value)) %>% pull(n) |
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if (input$dbtype == "OV"){ |
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pop_sp <- rename(pop_sp, "samples"="sample") |
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} |
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if (input$dbtype %in% c("UM", "CC")){ |
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pop_sp <- rename(pop_sp, "CODIGO"="sample") |
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} |
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pop_sql<-sqlFetch(dta, "IC") %>% slice(0) |
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pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql)) |
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for (id in names){ |
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print(id) |
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iso<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("iso|Iso|ISO",sampleNames(gs))] |
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ab<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("ab|Ab|AB",sampleNames(gs))] |
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g1<-ggcyto_arrange(autoplot(gs[[ab]], nodes_parent, bins=128), nrow=1) |
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g2<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd8, bins=64), nrow=1) |
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g3<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd8, bins=64), nrow=1) |
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g4<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd4, bins=64), nrow=1) |
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g5<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd4, bins=64), nrow=1) |
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g_all<-gridExtra::gtable_rbind(g1,g2,g3,g4,g5) |
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ggsave(paste0(route,id,".IC.png"), g_all, width = 10, height = 10) |
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if (input$dbtype == "OV"){ |
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data<-pop_sp %>% filter(samples == id) |
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data1<-data %>% gather(phen, value, -samples, -Population) |
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} |
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if (input$dbtype %in% c("UM", "CC")){ |
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data<-pop_sp %>% filter(CODIGO == id) |
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data1<-data %>% gather(phen, value, -CODIGO, -Population) |
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} |
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data1$phen<-gsub("p","+",data1$phen) |
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data1$phen<-gsub("n","-",data1$phen) |
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data1$phen<-gsub("_"," ",data1$phen) |
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data1$phen<-gsub("n","-",data1$phen, fixed = T) |
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data1$phen<-gsub("p","+",data1$phen, fixed = T) |
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data1$phen<-gsub("_"," ",data1$phen) |
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data1[data1$value < 0.5, "phen"]<-"Other" |
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data1$phen<-gsub("[A-Z]*-*[0-9T]- *", "", data1$phen) |
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data1$phen<-gsub("+ $", "", data1$phen) |
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data1$phen[data1$phen == ""]<-"All Negative" |
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# data1<-data1 %>% filter(value > 0.5) |
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data1["phen1"]<-"PD1" |
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data1[!grepl("PD1+", data1$phen),"phen1"]<-NA |
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data1["phen2"]<-"TIM3" |
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data1[!grepl("TIM3+", data1$phen),"phen2"]<-NA |
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data1["phen3"]<-"CTLA4" |
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data1[!grepl("CTLA4+", data1$phen),"phen3"]<-NA |
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data1["phen4"]<-"TIGIT" |
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data1[!grepl("TIGIT+", data1$phen),"phen4"]<-NA |
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data1["phen5"]<-"LAG3" |
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data1[!grepl("LAG3+", data1$phen),"phen5"]<-NA |
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data1<-data1 %>% arrange(desc(value)) |
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data2<-data1 %>% filter(!phen %in% c("All Negative","Other")) |
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data1<-rbind(data2, data1 %>% filter(phen %in% c("All Negative","Other")) %>% arrange(desc(phen))) |
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data_cd8<-data1 %>% filter(Population == "CD8") |
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data_cd4<-data1 %>% filter(Population == "CD4") |
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data_cd8$ymax<-cumsum(data_cd8$value) |
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data_cd8$ymin<-c(0, head(data_cd8$ymax, n=-1)) |
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data_cd4$ymax<-cumsum(data_cd4$value) |
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data_cd4$ymin<-c(0, head(data_cd4$ymax, n=-1)) |
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data1<-rbind(data_cd8, data_cd4) |
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color<-c(c("CTLA4+ LAG3+ PD1+ TIGIT+ TIM3+"="black","All Negative"="grey90","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E","TIGIT+"="#FA7055"), |
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c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F","PD1+ TIGIT+"="#D259AA", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "CTLA4+ TIGIT+"="#9C929A", "LAG3+ TIM3+"="#9ED848", "TIGIT+ TIM3+"="#ACB353", "LAG3+ TIGIT+"="#EC964A"), |
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c("CTLA4+ PD1+ TIGIT+"="#B86B6A","CTLA4+ PD1+ TIGIT+ TIM3+"="#B81515","LAG3+ PD1+ TIGIT+"="#007D8A", "PD1+ TIGIT+ TIM3+"="#D64545", "LAG3+ PD1+ TIGIT+ TIM3+"="#0f5860", "LAG3+ TIGIT+ TIM3+"="#50cad3")) |
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basic.color<-color[c("PD1+","TIGIT+","TIM3+","CTLA4+","LAG3+")] |
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names(basic.color)<-c("PD1","TIGIT","TIM3","CTLA4","LAG3") |
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# Make the plot |
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g_coex<-ggplot(data1)+ |
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facet_grid(factor(Population, levels=c("CD8","CD4"))~.)+ |
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=4.5, xmin=0), fill=color[data1$phen])+ |
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.4, xmin=5, fill=factor(phen1, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+ |
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.9, xmin=5.5, fill=factor(phen4, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+ |
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.4, xmin=6, fill=factor(phen2, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+ |
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.9, xmin=6.5, fill=factor(phen3, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+ |
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=7.4, xmin=7, fill=factor(phen5, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+ |
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scale_fill_manual(values = basic.color, na.value="#FFFFFF00", drop=F, limits=c("PD1","TIGIT","TIM3","CTLA4","LAG3"), name="IC")+ |
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coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially |
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xlim(c(0, 8)) +# Try to remove that to see how to make a pie chart |
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theme_classic()+ |
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theme(strip.background = element_blank(), |
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strip.text = element_text(size=12, face="bold"), |
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axis.line = element_blank(), |
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axis.ticks = element_blank(), |
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# plot.margin = margin(-200,0,0,0), |
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axis.text = element_blank()) |
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# g1<-ggcyto_arrange(autoplot(gs[[ab]], nodes_parent, bins=128), nrow=1) |
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# g2<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd8, bins=64), nrow=1) |
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# g3<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd8, bins=64), nrow=1) |
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# g4<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd4, bins=64), nrow=1) |
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# g5<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd4, bins=64), nrow=1) |
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g1<-ggcyto_arrange(autoplot(gs[[ab]], nodes_parent), nrow=1) |
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g2<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd8), nrow=1) |
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g3<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd8), nrow=1) |
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g4<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd4), nrow=1) |
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g5<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd4), nrow=1) |
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g_dots<-gridExtra::gtable_rbind(g1,g2,g3,g4,g5) |
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g_all<-ggpubr::ggarrange(g_dots, g_coex, nrow=1, widths=c(0.65,0.35)) |
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ggsave(paste0(route,id,".IC.png"), g_all, width = 14, height = 10) |
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} |
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} |
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}) |
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@ -1136,13 +1284,26 @@ server <- function(input, output) { |
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pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net) |
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pop_sp$CTLA4n_LAG3n_PD1n_TIGITn_TIM3n<- pop_sp %>% select(-CTLA4n_LAG3n_PD1n_TIGITn_TIM3n) %>% group_by(sample,Population) %>% |
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gather(pop, value, -sample,-Population) %>% summarise(n=100-sum(value)) %>% pull(n) |
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pop_sp <- rename(pop_sp, "samples"="sample") |
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if (input$dbtype == "OV"){ |
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pop_sp <- rename(pop_sp, "samples"="sample") |
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} |
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if (input$dbtype %in% c("UM", "CC")){ |
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pop_sp <- rename(pop_sp, "CODIGO"="sample") |
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} |
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pop_sql<-sqlFetch(dta, "IC") %>% slice(0) |
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pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql)) |
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vartypes<-rep("Number", pop_sp %>% select(-samples, -Population) %>% colnames %>% length) |
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names(vartypes)<-pop_sp %>% select(-samples, -Population) %>% colnames |
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if (input$dbtype == "OV"){ |
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vartypes<-rep("Number", pop_sp %>% select(-samples, -Population) %>% colnames %>% length) |
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names(vartypes)<-pop_sp %>% select(-samples, -Population) %>% colnames |
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} |
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if (input$dbtype %in% c("UM", "CC")){ |
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vartypes<-rep("Number", pop_sp %>% select(-CODIGO, -Population) %>% colnames %>% length) |
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names(vartypes)<-pop_sp %>% select(-CODIGO, -Population) %>% colnames |
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} |
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sqlSave(dta, pop_sp, tablename="IC", append = T, varTypes = vartypes, rownames = F) |
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print("Tabla IC sincronizada.") |
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