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3 Commits
| Author | SHA1 | Date | |
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| 88e2ab7664 | |||
| 5ab5ab4445 | |||
| 4f2d81ac5a |
+54
-46
@@ -374,30 +374,7 @@ server <- function(input, output) {
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oneside<-""
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oneside<-""
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table<-analysis$taula
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table<-analysis$taula
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if ("ID.animal" %in% colnames(table)){table<-rename(table, "ID animal"=`ID.animal`)}
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if ("ID" %in% colnames(table)){table<-rename(table, "ID animal"=ID)}
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if ("ID.tumor" %in% colnames(table)){table<-rename(table, "ID tumor"=`ID.tumor`)}
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# table[table$ID.tumor == "R","0"]<-NA
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col_nodays<-c("ID","Code", "Cage","Group", "ID.animal","ID animal", "ID.tumor", "ID tumor", "TS","DPV", "Absorbance")
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if (length(grep(0, colnames(table)[!colnames(table) %in% col_nodays])) == 0 & input$vacc == "Sí"){
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table["0"]<-0
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}
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table<-melt(table, id=colnames(table)[colnames(table) %in% col_nodays], variable.name = "Timepoint")
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table$Timepoint<-gsub("[A-Za-z ]","",table$Timepoint)
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# print(table)
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if ("DPV" %in% colnames(table)){
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table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~DPV, value.var = "value")
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table$Major<-table$Major
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table$Minor<-table$Minor
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table["Volume"]<-((table$Major*table$Minor*table$Minor)*(pi/6))
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}
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if ("TS" %in% colnames(table)){
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table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~TS, value.var = "value")
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table["Volume"]<-table$`TS-Deep`*table$`TS-Length`*table$`TS-Width`*pi/6
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}
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if (!"Volume" %in% colnames(table)){table<-rename(table, "Volume"=value)}
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table<-table %>% filter(!is.na(Group))
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table<-table %>% filter(!is.na(Group))
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table$Timepoint<-factor(table$Timepoint, levels=mixedsort(as.numeric(as.character(unique(table$Timepoint)))))
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if (input$increase_volume){
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if (input$increase_volume){
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timepoints<-unique(table$Timepoint)
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timepoints<-unique(table$Timepoint)
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table<-table %>% select(-Major, -Minor) %>%
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table<-table %>% select(-Major, -Minor) %>%
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@@ -406,30 +383,43 @@ server <- function(input, output) {
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gather(Timepoint, Volume, -Cage, -`ID animal`, -`ID tumor`, -Group) %>%
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gather(Timepoint, Volume, -Cage, -`ID animal`, -`ID tumor`, -Group) %>%
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mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
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mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
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}
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}
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table$Timepoint<-factor(table$Timepoint, levels=mixedsort(as.numeric(as.character(unique(table$Timepoint)))))
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table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n)
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analysis$taula_def<-table
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analysis$taula_vol<-dcast(table, Cage+`ID animal`+`ID tumor`~Timepoint,value.var = "Volume")
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table_plot<-dcast(dcast(table %>% filter(!is.na(Volume)), `ID animal`+Group+Timepoint~., value.var = "Volume", fun.aggregate = mean), Group~Timepoint)
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table_plot
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}
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}
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})
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})
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output$cin_group<-renderPlot({
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output$cin_group<-renderPlot({
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if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
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if (!is.null(input$file_analy) & !is.null(analysis$taula)){
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observeEvent(analysis$taula_def, {})
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observeEvent(analysis$taula, {})
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table<-analysis$taula_def
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table<-analysis$taula
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animals<-unique(table$Animal)
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sides<-unique(table$Side)
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groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
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basal<-data.frame(
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Cage="",
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Animal=rep(animals, each=length(sides)),
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Date="",
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DayPostInoc=0,
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Group=rep(groups, each=length(sides)),
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Side=rep(sides, length(animals)),
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Weight="",
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Long="",
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Wide="",
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Volume=0,
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Observations=""
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)
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table<-rbind(table, basal)
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if (input$vacc == "Sí"){
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if (input$vacc == "Sí"){
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ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
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ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
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geom_errorbar(stat="summary", width=0.05)+
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geom_errorbar(stat="summary", width=0.05)+
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geom_line(stat="summary")+
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geom_line(stat="summary")+
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geom_point(stat="summary")+
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geom_point(stat="summary")+
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facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
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facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
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labs(x="Days after tumor challenge")+
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labs(x="Days after tumor inoculation")+
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scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
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scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
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scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
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scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(table$DayPostInoc) / 5)+1)*5))+
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theme_bw()
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theme_bw()
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}else{
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}else{
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ggplot(table, aes(Timepoint, Volume, color=Group, group=Group))+
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ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
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geom_errorbar(stat="summary",width=0.05)+
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geom_errorbar(stat="summary",width=0.05)+
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geom_line(stat="summary")+
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geom_line(stat="summary")+
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geom_point(stat="summary")+
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geom_point(stat="summary")+
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@@ -442,29 +432,47 @@ server <- function(input, output) {
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}
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}
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})
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})
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output$cin_indiv<-renderPlot({
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output$cin_indiv<-renderPlot({
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if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
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if (!is.null(input$file_analy) & !is.null(analysis$taula)){
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observeEvent(analysis$taula_def, {})
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observeEvent(analysis$taula, {})
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table<-analysis$taula_def
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table<-analysis$taula
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print(table)
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animals<-unique(table$Animal)
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sides<-unique(table$Side)
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groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
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basal<-data.frame(
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Cage="",
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Animal=rep(animals, each=length(sides)),
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Date="",
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DayPostInoc=0,
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Group=rep(groups, each=length(sides)),
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Side=rep(sides, length(animals)),
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Weight="",
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Long="",
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Wide="",
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Volume=0,
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Observations=""
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)
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table<-rbind(table, basal)
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if (input$vacc == "Sí"){
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if (input$vacc == "Sí"){
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ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=`ID animal`))+
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ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Animal))+
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# geom_errorbar(stat="summary", width=0.05)+
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# geom_errorbar(stat="summary", width=0.05)+
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geom_line()+
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geom_line()+
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geom_point()+
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geom_point()+
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scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
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scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
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scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
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scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(table$DayPostInoc) / 5)+1)*5))+
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facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
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facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
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labs(x="Days after tumor challenge")+
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labs(x="Days after tumor inoculation")+
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theme_bw()
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theme_bw()
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}else{
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}else{
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ggplot(table, aes(Timepoint, Volume, color=Group, group=paste0(`ID animal`, `ID tumor`)))+
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ggplot(table, aes(DayPostInoc, Volume, color=Group, group=paste0(Animal, Side)))+
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# geom_errorbar(stat="summary", width=0.05)+
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# geom_errorbar(stat="summary", width=0.05)+
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geom_line()+
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geom_line()+
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geom_point()+
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geom_point()+
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scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
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scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
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# scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
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# scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
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facet_wrap(.~Group)+
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facet_wrap(.~Group)+
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labs(x="Days after tumor challenge")+
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labs(x="Days after tumor inoculation")+
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theme_bw()+
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theme_bw()+
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theme(axis.text.x=element_text(angle=45, hjust=1))
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theme(axis.text.x=element_text(angle=45, hjust=1))
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}
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}
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