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He empezado a incorporar el triangular la matriz.

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Costa
2022-02-04 15:32:12 +01:00
parent 6e6d01b3fc
commit d51fe8a64d
1 changed files with 14 additions and 5 deletions
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R/ggcorrplot.R
+14 -5
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@@ -1,12 +1,21 @@
ggcorrplot<-function(df, var, color="#FFFFFF00", stat="signif"){ ggcorrplot<-function(df, var, color="#FFFFFF00", stat="signif", tri="all"){
m.df<-df %>% spread(Cyt, Value) %>% select(-pats) m.df<-df %>% spread(Cyt, Value) %>% select(-pats)
mcor<-cor(m.df, m.df, use="pairwise.complete.obs") # Por defecto usa el método de Pearson. mcor<-cor(m.df, m.df, use="pairwise.complete.obs") # Por defecto usa el método de Pearson.
mpval<-Hmisc::rcorr(as.matrix(m.df))$P mpval<-Hmisc::rcorr(as.matrix(m.df))$P
df<-mcor %>% as.data.frame() %>% add_column(Var1=rownames(mcor),.before=1) %>% df<-mcor %>% as.data.frame()
gather(Var2, Value, -Var1) if (tri == "lower"){
df.pval<-mpval %>% as.data.frame() %>% add_column(Var1=rownames(mpval),.before=1) %>% df[lower.tri(df, diag=T)]<-NA
gather(Var2, Value, -Var1) }
df<-df %>% add_column(Var1=rownames(mcor),.before=1) %>%
gather(Var2, Value, -Var1) %>% filter(!is.na(Value))
df.pval<-mpval %>% as.data.frame()
if (tri == "lower"){
df.pval[lower.tri(df.pval, diag=T)]<-NA
}
df.pval<-df.pval %>% add_column(Var1=rownames(mpval),.before=1) %>%
gather(Var2, Value, -Var1) %>% filter(!is.na(Value))
df.pval$Value<-round(df.pval$Value, 3) df.pval$Value<-round(df.pval$Value, 3)