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74 lines
4.2 KiB
74 lines
4.2 KiB
ggstats_add_xy_test<-function(table_stat, table, xcol=NULL, group, y="max", bracket.offset=0.05, bracket.inspace=0.05, exclude_group=NULL){
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## Adapted version to fit rstatix output
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value.var<-table_stat[[1,".y."]]
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if (is.null(xcol)){
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x<-colnames(table_stat)[1]
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}else{x<-xcol}
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if(!is.null(group)){table[,group]<-as.factor(table[,group])}
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table[,x]<-as.factor(table[,x])
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if (is.null(exclude_group)){
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table_agg<-table %>% group_by(.data[[x]])
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}else{
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table_agg<-table %>% group_by(.data[[x]], .data[[exclude_group]])
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}
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if (y == "max"){
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agg<-table_agg %>% summarise(max=max(.data[[value.var]]))
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if(!is.na(exclude_group)){agg<-table_agg %>% group_by(.data[[exclude_group]]) %>% summarise(max=max(.data[[value.var]]))}
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}else if (y == "mean"){
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agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]])) %>% spread(group, mean)
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agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
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colnames(agg)[1]<-x
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}else if (y == "mean+sd"){
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agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]])+sd(.[[value.var]])) %>% spread(group, mean)
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agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
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colnames(agg)[1]<-x
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}else if (y == "mean+sem"){
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agg<-table %>% group_by(.data[[x]],.data[[group]]) %>% summarise(mean=mean(.data[[value.var]])+sem(.[[value.var]])) %>% spread(group, mean)
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agg<- data.frame(x=agg[,1], "max"=apply(agg[,2:ncol(agg)], 1, max, na.rm=T))
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colnames(agg)[1]<-x
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}
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group.list<-list()
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count<-1
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if(!is.null(group)){table_stat<-mutate(table_stat, {{x}}:=as.factor(.data[[x]]))}
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for (i in 1:nrow(table_stat)){
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group.list[[count]]<-c(table_stat %>% slice(i) %>% pull(group1),table_stat%>% slice(i) %>% pull(group2))
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count<-count+1
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}
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if(!is.null(group)){
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x.index<-sapply(table_stat %>% pull(x), function(y) which(levels(table_stat %>% pull(x)) == y))
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t<-tibble("y.position"=merge(table_stat, agg ,sort=F)[,"max"]+diff(range(table[value.var], na.rm = T))*bracket.offset,
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"groups"=group.list,
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"x.temp"=x.index,
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"xmin"=(match(table_stat %>% pull(x), levels(table[,x]))+0.75*((match(table_stat$group1, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5)),
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"xmax"=match(table_stat %>% pull(x), unique(table[,x]))+0.75*((match(table_stat$group2, levels(table[,group]))-0.5)/length(levels(table[,group]))-0.5)
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) %>% rename("x"="x.temp")
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}else{
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t<-tibble("y.position"=merge(table_stat, agg ,sort=F)[,"max"]+diff(range(table[value.var], na.rm = T))*bracket.offset,
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"groups"=group.list,
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# "x.temp"=x.index,
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)# %>% rename("x"="x.temp")
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}
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if (!is.null(group)){
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if (!is.null(exclude_group)){
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for (j in unique(pull(table_stat, all_of(exclude_group)))){
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for (dia in unique(pull(table_stat,all_of(xcol)))){
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if (stat.test %>% filter(p < 0.05) %>% filter(.data[[x]] == dia & .data[[exclude_group]] == j) %>% nrow() > 0){
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t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"]<-seq(t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]],
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t[table_stat[,x] == dia & table_stat[,exclude_group] == j,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia & table_stat[,exclude_group] == j,])-1),
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by=diff(range(table[,value.var], na.rm = T))*bracket.inspace)
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}
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}
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}
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}else{
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for (dia in unique(pull(table_stat,all_of(xcol)))){
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t[table_stat[,x] == dia,"y.position"]<-seq(t[table_stat[,x] == dia,"y.position"][[1,1]],
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t[table_stat[,x] == dia,"y.position"][[1,1]]+diff(range(table[,value.var], na.rm = T))*bracket.inspace*(nrow(table_stat[table_stat[,x] == dia,])-1),
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by=diff(range(table[,value.var], na.rm = T))*bracket.inspace)
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}
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}
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}
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return(cbind(table_stat,t) %>% as_tibble)
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}
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