Fig. 1
From: Robust principal component analysis for accurate outlier sample detection in RNA-Seq data
Comparing the performance of cPCA and rPCA on the simulated data. a cPCA plot of the simulated baseline data with two treatment groups and 3 biological replicates each. The first principal component captured the variation of the baseline samples between the two groups. b cPCA plot of the simulated baseline data plus outlierL1; The first principal component was attracted by outlierL1. c cPCA plot of the simulated baseline data plus outlierH1; The first principal component was attracted by outlierH1. d-f Outlier maps of the simulated baseline plus outlierL1 data set using (d) cPCA, (e) PcaGrid and (f) PcaHubert. (g-i) Outlier maps of the simulated baseline plus outlierH1 data set using (g) cPCA, (h) PcaGrid and (i) PcaHubert. OutlierL1: simulated sample L-1 of the low “outlierness” group. OutlierH1: simulated sample H-1 of the high “outlierness” group. Sample 5: the 5th sample of the baseline data set