I have a data.frame from a rna-seq experiment, and I would like to remove some outliers. The data is huge with 350 samples and 32291 genes. The data are log2 RPKM values (I did the log2 because I am planning to do
WGCNA analysis and the authors recommend to make a log2 transformation of the data).
I am using the
PcaHubert function from
rrcov package to find outliers, here is the code I am using:
df <- read.table("/path/to/file/rpkm.txt") dim(df) #32291 352 df <- df[,-c(1,2)] # first 2 columns have accessory data library(rrcov) pcaHub <- PcaHubert(t(df)) outliers <- which(pcaHub@flag=='FALSE')
The outliers would be those samples with the flag
FALSE after doing the RobustPCA, do you think it is appropriate to remove outliers using this method?
Any comments would be greatly appreciated
Hello There is this parameter "crit.pca.distances" in function PcaHubert what should be the value for this other than default value. And what is this parameter?