I have a PCA plot with a lot of data and I want to identify which samples are the outliers. When I use
geom.ind = c("text")
then there is so much text that I can´t read anything.
Here is a minimal reproducible example. (I already used it here tooltip with names in a PCA plot but the answer only works manually and I really have a great dataframe)
dataframe <- data_frame("c1"=c(78,89,0),"c2"=c(89,89,34),"c3"=c(56,0,4))
row.names(dataframe) <- c("name1","name2","name3")
sub <- PCA(dataframe)
pca <- fviz_pca_ind(sub, pointsize = "cos2",
pointshape = 21, fill = "#E7B800",
repel = TRUE, # Avoid text overlapping (slow if many points)
geom = c("text","point"),
xlab = "PC1", ylab = "PC2",label = row.names(dataframe)
)
interactive <- ggplotly(pca,dynamicTicks = T,tooltip = c("x","y",label = list))
As you can see, I treid to do it with ggplotly() function but that does not work.
I want to identify the sample name (name1,name2,name3) in my plot. How can I do this for a great dataset?
Thank you so much in advance
You can use the following code
library(tidyverse)
library("factoextra")
library(plotly)
library(FactoMineR)
dataframe <- data_frame("c1"=c(78,89,0),"c2"=c(89,89,34),"c3"=c(56,0,4))
row.names(dataframe) <- c("name1","name2","name3")
sub <- PCA(dataframe)
pca <- fviz_pca_ind(sub, pointsize = "cos2",
pointshape = 21, fill = "#E7B800",
repel = TRUE, # Avoid text overlapping (slow if many points)
geom = c("text","point"),
xlab = "PC1", ylab = "PC2",label = c("ind")
)
interactive <- ggplotly(pca,tooltip = c("x","y","colour"))
bggly <- plotly_build(interactive)
bggly$x$data[[1]]$text <-
with(pca$data, paste0("name: ", name,
"</br></br>x: ", x,
"</br>y: ", y,
"</br>coord: ", coord,
"</br>cos2: ", cos2,
"</br>contrib: ", contrib))
bggly
After taking help from this post by Stéphane Laurent.
For large dataset in .csv format with 1st column as row names, you can read in it as df <- read.csv("Test_Data.csv", row.names = 1)
, provided your row names are not duplicated.