Sparse PCA for compositional data

A great number of procedures for sparse principal component analysis (PCA) were proposed in the last decade. However, they cannot be applied directly for PCA of compositional data (CoDa). We introduce a new procedure for sparse PCA which takes into account the additional constraints specific for CoDa. The proposed method is very effective to find logcontrasts in data, which is illustrated on a real example.