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My data matrix has 100 rows and 900 columns. Here each row represents a IR spectra. The column represents the wavenumbers. The first 23 rows belong to different IR spectra from the same sample (i.e spectra from 23 different positions in the sample). Similarly I have measured 5 samples each with certain no.of observations. For ex: 1-23 rows belongs to sample 1, 24:40 belongs to sample 2. Now I want to colour the scores in my PCA score plot according to the sample colours and label the colour with the sample name. Like, 23 scores in blue and then a label referring Sample 1.

I have added an extra column named label, to my data matrix referring the sample names. But I do not how to proceed further?

Abzer Kelmina
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1 Answers1

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I was using the packages "factoextra", "sf" for this. Here df is the data frame that contains the data for PCA. Here I added another column referring to the labels of my data. In the code,col.ind= df$lab.id says that I have taken the labelling id (labels) as the color index. Hence in the resulting PCA score plot, my scores were colour coded according to their labels.

fviz_pca_ind(PCA,axes=c(1,2),title="PC1 vs PC2",label="none",geom.ind="point",col.ind=df$lab.id,palette="lancet",addEllipses=FALSE, ellipse.level=0.95,pointsize=2,
             repel = TRUE,   # Avoid text overlapping,
             legend.title="Disease ",mean.point=FALSE,xlab=paste0("PC1: ",round(Variance_xplained[1]*100,1),"%"),ylab=paste0("PC2: ",round(Variance_xplained[2]*100,1),"%")

)
Abzer Kelmina
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