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BACOM is a statistically principled and unsupervised method that detects copynumber deletion types (homozygous versus heterozygous), estimates normal cellfraction, and recovers cancer specific copy number profiles, using allelespecific copy number signals. In a subsequent analysis of TCGA ovarian cancerdataset, the average normal cell fraction estimated by BACOM was found higherthan expected. In this letter, we first discuss the advantages of the BACOM inrelation to alternative approaches. Then, we show that this elevated estimateof normal cell fraction is the combined result of inaccurate signal modelingand normalization. Lastly, we describe an allele specific signal modeling andnormalization scheme that can enhance BACOM applications in many biologicalcontexts. An open source MATLAB program was developed to implement our extendedmethod and it is publically available.

BACOM 2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor