This study presents an allele-specific copy number analysis of the in vivo breast cancer genome using the ASCAT (allele-specific copy number analysis of tumors) algorithm. ASCAT allows accurate estimation of allele-specific copy numbers in solid tumors, accounting for tumor ploidy and nonaberrant cell admixture. This method enables the calculation of genome-wide allele-specific copy-number profiles, which can accurately determine gains, losses, copy number-neutral events, and loss of heterozygosity (LOH). In an early-stage breast carcinoma series, 45% of cases showed aneuploidy (>2.7n) and an average nonaberrant cell admixture of 49%. Aggregation of ASCAT profiles across the series revealed genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. ASCAT profiles also revealed differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between five molecular breast cancer subtypes. Basal-like breast carcinomas had a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles showed large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. From the ASCAT profiles, a genome-wide map of allelic skewness in breast cancer was constructed, indicating loci where one allele is preferentially lost, whereas the other is preferentially gained. The study hypothesizes that these alternative alleles have different influences on breast carcinoma development. The ASCAT algorithm was validated using various methods, including dilution series of tumor samples mixed with germline DNA, experimental determination of DNA content in tumor cells, and FISH experiments. The results show that ASCAT accurately predicts tumor ploidy and allele-specific copy numbers, even in cases with high nonaberrant cell admixture. The study highlights the importance of considering tumor aneuploidy and nonaberrant cell admixture in the analysis of cancer genomes. ASCAT profiles allow accurate dissection of gains, losses, LOH, and copy number-neutral events, providing insights into tumor development. The study also identifies characteristic differences in tumor ploidy, non-aberrant cell admixture, and frequency of gains, losses, LOH, and copy number-neutral events among the five molecularly defined breast cancer subtypes. These findings confirm the added value of the ASCAT approach and support the hypothesis that these molecular subtypes are distinct biological entities. The study also provides insights into tumor development, showing that Luminal A breast carcinomas are typically diploid with limited aberrations, while Basal-like carcinomas show numerous aberrations with a ploidy of 1.6n to 2n, followed by a whole-genome duplication. The study concludes that ASCAT profiles are useful tools for interpreting cancer genome data, aiding in the assemblyThis study presents an allele-specific copy number analysis of the in vivo breast cancer genome using the ASCAT (allele-specific copy number analysis of tumors) algorithm. ASCAT allows accurate estimation of allele-specific copy numbers in solid tumors, accounting for tumor ploidy and nonaberrant cell admixture. This method enables the calculation of genome-wide allele-specific copy-number profiles, which can accurately determine gains, losses, copy number-neutral events, and loss of heterozygosity (LOH). In an early-stage breast carcinoma series, 45% of cases showed aneuploidy (>2.7n) and an average nonaberrant cell admixture of 49%. Aggregation of ASCAT profiles across the series revealed genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. ASCAT profiles also revealed differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between five molecular breast cancer subtypes. Basal-like breast carcinomas had a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles showed large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. From the ASCAT profiles, a genome-wide map of allelic skewness in breast cancer was constructed, indicating loci where one allele is preferentially lost, whereas the other is preferentially gained. The study hypothesizes that these alternative alleles have different influences on breast carcinoma development. The ASCAT algorithm was validated using various methods, including dilution series of tumor samples mixed with germline DNA, experimental determination of DNA content in tumor cells, and FISH experiments. The results show that ASCAT accurately predicts tumor ploidy and allele-specific copy numbers, even in cases with high nonaberrant cell admixture. The study highlights the importance of considering tumor aneuploidy and nonaberrant cell admixture in the analysis of cancer genomes. ASCAT profiles allow accurate dissection of gains, losses, LOH, and copy number-neutral events, providing insights into tumor development. The study also identifies characteristic differences in tumor ploidy, non-aberrant cell admixture, and frequency of gains, losses, LOH, and copy number-neutral events among the five molecularly defined breast cancer subtypes. These findings confirm the added value of the ASCAT approach and support the hypothesis that these molecular subtypes are distinct biological entities. The study also provides insights into tumor development, showing that Luminal A breast carcinomas are typically diploid with limited aberrations, while Basal-like carcinomas show numerous aberrations with a ploidy of 1.6n to 2n, followed by a whole-genome duplication. The study concludes that ASCAT profiles are useful tools for interpreting cancer genome data, aiding in the assembly