library(dplyr) library(dunn.test) library(tibble) library(reshape2) library(ggplot2) corr_multi<-function(table, genes1, genes2, font_size=5, ruta="./", exportar=F) { cor.list<-list() cont<-1 for (gene1 in genes1){ for (gene2 in genes2){ print(gene1) print(gene2) cor_temp<-cor.test(table[,gene1], table[,gene2]) if (!is.na(cor_temp$p.value)){ pval_plot<-paste("cor =",format(cor_temp$estimate, digits=2),if(cor_temp$p.value < 2.2e-16){" , p < 2.2e-16"}else{paste(", p=",format(cor_temp$p.value,digits=3))}) } cor.list[[cont]]<-ggplotGrob(ggplot(data=table, aes(x=table[,gene1], y=table[,gene2]))+ geom_point()+ geom_smooth(method="lm")+ geom_text(aes(x=min(table[,gene1], na.rm=T), y=(max(table[,gene2],na.rm = T)+max(table[,gene2],na.rm = T)*0.2), label=pval_plot), hjust="inward", family="serif", size=font_size)+ labs(x=gene1, y=gene2)+ theme_bw()) if (exportar == T){ png(paste0(ruta,gene1,"vs",gene2,".png"), res=900, width=3000, height=3000) plot(cor.list[[cont]]) dev.off() } cont<-cont+1 } } return(cor.list) } multi_stats<-function(table, value.var, x, group, stat.test, adjust="default", paired=F){ ## Requires dplyr and tibble packets defaults=c("dunn"="none", "ttest"="holm", "wilcox"="holm") funs<-c("ttest"="pairwise.t.test", "wilcox"="pairwise.wilcox.test") if (adjust == "default"){adjust=defaults[stat.test]} stat.def<-as.data.frame(matrix(nrow=0, ncol=5)) colnames(stat.def)<-c(x, "group1", "group2", "p.adj", "p.signif") for (point in unique(table[,x])){ condition<-all(table %>% filter(table[,x] == point) %>% pull(value.var) == 0) == F len_group<-length(unique(table %>% filter(table[,x] == point) %>% pull(group))) if (condition == T & !is.na(condition) & len_group > 1){ if(stat.test == "dunn"){ test<-dunn.test(table %>% filter(table[,x] == point) %>% pull(value.var), table %>% filter(table[,x] == point) %>% pull(group), method=adjust) comp<-strsplit(test$comparisons, " - ") stat.temp<-data.frame(matrix(unlist(comp), nrow=length(comp), byrow=T), "p.adj"=test$P.adjusted, stringsAsFactors = F, check.names = F) colnames(stat.temp)[1:2]<-c("group1", "group2") }else if (stat.test %in% names(funs)){ test<-get(funs[stat.test])(table %>% filter(table[,x] == point) %>% pull(value.var), table %>% filter(table[,x] == point) %>% pull(group), method=adjust, paired=paired)$p.value stat.temp<-melt(test) colnames(stat.temp)<-c("group1", "group2","p.adj") } stat.temp["p.signif"]<-case_when( stat.temp$p.adj >= 0.05 ~ "ns", stat.temp$p.adj < 0.0001 ~ "****", stat.temp$p.adj < 0.001 ~ "***", stat.temp$p.adj < 0.01 ~ "**", stat.temp$p.adj < 0.05 ~ "*" ) stat.temp<-stat.temp %>% add_column(x=point, .before=T) colnames(stat.temp)[1]<-x stat.def<-rbind(stat.def, stat.temp) } } stat.def["Method"]<-stat.test return(stat.def) } generate_labstats<-function(table_stat, table, value.var, x, group, y="max", bracket.offset=0.05, bracket.length=0.02){ table[,group]<-as.factor(table[,group]) table[,x]<-as.factor(table[,x]) se<-function(x, na.rm=F) sd(x, na.rm = na.rm)/sqrt(length(x)) if (y == "max"){ formula<-as.formula(paste0(colnames(table_stat)[1], "~.")) agg<-dcast(table, formula, value.var = value.var, fun.aggregate = max, na.rm=T) }else if (y == "mean"){ formula<-as.formula(paste0(colnames(table_stat)[1], "~", group)) agg<-dcast(table, formula, value.var = value.var, fun.aggregate = mean, na.rm=T) agg<- data.frame(x=agg[,1], "."=apply(agg[,2:ncol(agg)], 1, max, na.rm=T)) colnames(agg)[1]<-x }else if (y == "mean+sd"){ formula<-as.formula(paste0(colnames(table_stat)[1], "~", group)) agg<- dcast(table, formula, value.var = value.var, fun.aggregate = function(x) mean(x,na.rm=T)+sd(x,na.rm=T)) agg<- data.frame(x=agg[,1], "."=apply(agg[,2:ncol(agg)], 1, max, na.rm=T)) colnames(agg)[1]<-x }else if (y == "mean+se"){ formula<-as.formula(paste0(colnames(table_stat)[1], "~", group)) agg<- dcast(table, formula, value.var = value.var, fun.aggregate = function(x) mean(x,na.rm=T)+se(x,na.rm=T)) agg<- data.frame(agg[,1], "."=apply(agg[,2:ncol(agg)], 1, max, na.rm=T)) colnames(agg)[1]<-x } t<-data.frame("y1"=merge(table_stat, agg ,sort=F)[,"."]+diff(range(table[value.var], na.rm = T))*bracket.offset, "y2"=merge(table_stat, agg ,sort=F)[,"."]+diff(range(table[value.var], na.rm = T))*bracket.offset, "x1"= match(table_stat[,x], unique(table[,x]))+ 0.75*((match(table_stat$group1, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5), "x2"= match(table_stat[,x], unique(table[,x]))+ 0.75*((match(table_stat$group2, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5) ) for (dia in unique(table_stat[,1])){ t[table_stat[,x] == dia,"y1"]<-seq(t[table_stat[,x] == dia,"y1"][1], t[table_stat[,x] == dia,"y1"][1]+diff(range(table[,value.var], na.rm = T))*0.05*(nrow(table_stat[table_stat[,x] == dia,])-1), by=diff(range(table[,value.var], na.rm = T))*0.05) t[table_stat[,x] == dia,"y2"]<-t[table_stat[,x] == dia,"y1"] } t_def<-as.data.frame(matrix(ncol=4, nrow=0)) for (row in 1:nrow(t)){ t_def<-rbind(t_def, t[row,], c(t[row,"y1"]-diff(range(table[,value.var], na.rm = T))*bracket.length, t[row,"y1"], t[row,"x1"], t[row,"x1"]), c(t[row,"y1"]-diff(range(table[,value.var], na.rm = T))*bracket.length, t[row,"y1"], t[row,"x2"], t[row,"x2"])) } t_lab<-data.frame("x"=t$x1+(t$x2-t$x1)/2, "y"=t$y1+diff(range(table[,value.var], na.rm = T))*0.005, check.names = F) return(list("label"=t_lab, "brackets"=t_def)) } secfile<-function(file){ ext<-strsplit(file, ".", fixed = T)[[1]] ext<-ext[length(ext)] num<-1 while(file.exists(file) == T){ if(num == 1){ file_tmp<-strsplit(file, ".", fixed=T)[[1]] file<-paste0(paste(file_tmp[1:(length(file_tmp)-1)], collapse = "."),"_",num,".",file_tmp[length(file_tmp)]) }else{ file_tmp<-paste(strsplit(file, "_", fixed=T)[[1]][-length(strsplit(file, "_", fixed=T)[[1]])], collapse = "_") file<-paste0(file_tmp, "_", num,".",ext) } num<-num+1 } return(file) }