Analysis of proteomics data: Block $k$-mean alignment

Abstract

We analyze the proteomics data introducing a block $k$-mean alignment procedure. This technique is able to jointly align and cluster the data, accounting appropriately for the block structure of these data, that includes measurement repetitions for each patient. An analysis of area-under-peaks, following the alignment, separates patients who respond and those who do not respond to treatment.