Detectar si hay pestaña para sexo de los ratones y adaptarse.
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+41
-23
@@ -1,8 +1,6 @@
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library(shiny)
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# library(ggplot2)
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library(reshape2)
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library(openxlsx)
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# library(dplyr)
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library(car)
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library(ggbeeswarm)
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library(gtools)
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@@ -104,7 +102,9 @@ server <- function(input, output) {
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}
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dades$taula<-taula
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dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = 2, colName=F)[,1]
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dades$sex<-read.xlsx(input$file_sizes$datapath, sheet = 3, sep.names = " ")
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if (readxl::excel_sheets(input$file_sizes$datapath) %>% length > 2){
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dades$sex<-read.xlsx(input$file_sizes$datapath, sheet = 3, sep.names = " ")
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}
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}
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})
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output$firstPlot <- renderPlot({
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@@ -150,7 +150,12 @@ server <- function(input, output) {
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low_cuttof<-input$lowcut
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# print(up_cuttof)
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df<-df[df$Volume < up_cuttof & df$Volume >= low_cuttof,]
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df<-merge(df, dades$sex)
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if (is.null(dades$sex)){
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df<-add_column(df, sex="undefined")
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}else{
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df<-merge(df, dades$sex)
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}
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# df["Mouse"]<-gsub("[a-zA-Z]", "", df$MouseID)
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# print(df$Volume)
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@@ -159,7 +164,7 @@ server <- function(input, output) {
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ngroup<-length(dades$groups)
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df_def<-list()
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# print(head(df))
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for (sex.var in c("male","female")){
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for (sex.var in unique(df$sex)){
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# print(sex.var)
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df_sex<-df %>% filter(`sex` == sex.var)
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ind.list<-list()
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@@ -194,33 +199,46 @@ server <- function(input, output) {
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# print(df_sex)
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df_def[[sex.var]]<-merge(df_sex %>% select(-group), ind.list[[index]])
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}
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# df_def<-do.call(rbind, c(df_def, make.row.names=F))
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df_def<-do.call(rbind, c(df_def, make.row.names=F))
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# lapply(df_def, function(x) x %>% as_tibble %>% print(n=Inf))
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df_def<-rbind(df_def[[1]], df_def[[2]], make.row.names=F)
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# df_def<-rbind(df_def[[1]], df_def[[2]], make.row.names=F)
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if ("Group" %in% colnames(df_def)){
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df_def<-df_def %>% select(-"Group")
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}
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df_def<-merge(merge(dades$taula, dades$sex) %>% select(-Group), df_def[,c("ID animal", "group")] %>% unique, all=T, by="ID animal") %>% select(c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))
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df_def<-merge(
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if(!is.null(dades$sex)){merge(dades$taula, dades$sex)}else{dades$taula %>% add_column(sex="undefined")} %>% select(-Group),
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df_def[,c("ID animal", "group")] %>% unique, all=T, by="ID animal") %>%
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select(c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))
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df_def[!paste0(df_def$`ID animal`, df_def$`ID tumor`) %in% paste0(df$`ID animal`, df$`ID tumor`),"group"]<-NA
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dades$db<-df_def
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ggarrange(
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ggplot(df_def, aes(group, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_jitter(width=0.25, aes(color=sex))+
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geom_point(stat="summary", color="blue", size=3)+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)),
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# lims(y=c(0,max(df_def$Volume)+10))
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ggarrange(
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ggplot(df_def, aes(sex, Volume))+
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if (is.null(dades$sex)){
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ggplot(df_def, aes(group, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_quasirandom(width=0.3),
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ggplot(df_def, aes(group, fill=sex))+
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geom_bar(stat="count", color="black", position="dodge")+
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guides(fill="none")+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)), ncol = 1, heights = c(0.35, 0.65)),
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nrow = 1, aligh="h", widths = c(0.65, 0.35))
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geom_jitter(width=0.25)+
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geom_point(stat="summary", color="blue", size=3)+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5))
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}else{
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ggarrange(
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ggplot(df_def, aes(group, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_jitter(width=0.25, aes(color=sex))+
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geom_point(stat="summary", color="blue", size=3)+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)),
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# lims(y=c(0,max(df_def$Volume)+10))
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ggarrange(
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ggplot(df_def, aes(sex, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_quasirandom(width=0.3),
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ggplot(df_def, aes(group, fill=sex))+
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geom_bar(stat="count", color="black", position="dodge")+
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guides(fill="none")+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)), ncol = 1, heights = c(0.35, 0.65)),
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nrow = 1, aligh="h", widths = c(0.65, 0.35))
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}
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})
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output$distPlot <- renderPlot({
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observeEvent(dades$taula, {})
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if (!is.null(dades$taula)){
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