How to extract the variable IDs after dimensionality reduction via pca?

I have a dataset X(voxel*protein), it's size is 3694200*10. I used pca to reduce dimensionality and got a matrix of size 3694200*4. The question is that I need to know which 4 proteins are remained. How can I get the original column IDs(0-9) of the 4 proteins?

My code: [COEEF,SCORE,LATENT] = pca(X); cumVar = cumsum(LATENT)./sum(LATENT); reducedData = SCORE(:,1:4);

Answer 1

[the cyclist]

PCA doesn't select a subset of variable. (Specifically, in your case, PCA does not select 4 out of your 10 variables).

Instead, PCA is identifying linear combinations of your original variables that explain the overall variation. If a small number of these linear combinations capture most of the variation, then it makes sense to limit to those combinations. The first output variable tells you the coefficients of those linear combinations.

[Bank Yin]

Exactly! My mistake.Thank you any way.