The paper introduces ABSOLUTE, a computational method to infer tumor purity and ploidy from somatic DNA alterations. It can detect subclonal heterogeneity and somatic homozygosity, and calculate statistical sensitivity for specific aberrations. Using ABSOLUTE, the authors analyzed 214 ovarian carcinoma tumor-normal pairs, identifying pervasive subclonal mutations and a small subset of clonal and homozygous mutations in genes like TP53 and NF1. ABSOLUTE also inferred absolute allelic copy-number profiles from 3,155 cancer specimens, revealing that genome-doubling events are common in human cancer, likely occurring in aneuploid cells and influencing tumor progression. ABSOLUTE addresses the challenge of measuring somatic copy-number alterations (SCNAs) in cancer samples by estimating absolute copy numbers per cancer cell, which is more accurate than relative measurements. This is crucial for understanding cancer genome structure and evolution. The method uses a mathematical framework to jointly estimate tumor purity and ploidy from observed copy profiles, and accounts for subclonal alterations. The authors validated ABSOLUTE using various methods, including FACS-based ploidy measurements, spectral karyotyping, and DNA-mixing experiments. Results showed that ABSOLUTE provided more accurate estimates of tumor purity and ploidy compared to other methods like ASCAT. ABSOLUTE was applied to analyze 3,155 cancer samples, revealing that genome doubling occurs frequently in cancer, often in cells already aneuploid. The study also analyzed subclonal evolution in ovarian cancer, identifying subclonal mutations and their implications for tumor progression. ABSOLUTE was used to classify mutations based on their multiplicity, revealing that certain genes like CDK12 are potential tumor suppressors. The method also showed that genome doubling is more common in epithelial cancers and is associated with increased age at diagnosis and cancer recurrence. The paper discusses the importance of ABSOLUTE in designing clinical sequencing studies and understanding cancer genome evolution. It highlights the role of genome doubling in cancer progression and the impact of subclonal mutations on tumor heterogeneity. The findings suggest that genome doubling may influence the selection of tumor suppressor inactivation events, and that subclonal mutations may play a key role in cancer development and response to therapy. The study provides a framework for further analysis of cancer genomes and their evolutionary trajectories.The paper introduces ABSOLUTE, a computational method to infer tumor purity and ploidy from somatic DNA alterations. It can detect subclonal heterogeneity and somatic homozygosity, and calculate statistical sensitivity for specific aberrations. Using ABSOLUTE, the authors analyzed 214 ovarian carcinoma tumor-normal pairs, identifying pervasive subclonal mutations and a small subset of clonal and homozygous mutations in genes like TP53 and NF1. ABSOLUTE also inferred absolute allelic copy-number profiles from 3,155 cancer specimens, revealing that genome-doubling events are common in human cancer, likely occurring in aneuploid cells and influencing tumor progression. ABSOLUTE addresses the challenge of measuring somatic copy-number alterations (SCNAs) in cancer samples by estimating absolute copy numbers per cancer cell, which is more accurate than relative measurements. This is crucial for understanding cancer genome structure and evolution. The method uses a mathematical framework to jointly estimate tumor purity and ploidy from observed copy profiles, and accounts for subclonal alterations. The authors validated ABSOLUTE using various methods, including FACS-based ploidy measurements, spectral karyotyping, and DNA-mixing experiments. Results showed that ABSOLUTE provided more accurate estimates of tumor purity and ploidy compared to other methods like ASCAT. ABSOLUTE was applied to analyze 3,155 cancer samples, revealing that genome doubling occurs frequently in cancer, often in cells already aneuploid. The study also analyzed subclonal evolution in ovarian cancer, identifying subclonal mutations and their implications for tumor progression. ABSOLUTE was used to classify mutations based on their multiplicity, revealing that certain genes like CDK12 are potential tumor suppressors. The method also showed that genome doubling is more common in epithelial cancers and is associated with increased age at diagnosis and cancer recurrence. The paper discusses the importance of ABSOLUTE in designing clinical sequencing studies and understanding cancer genome evolution. It highlights the role of genome doubling in cancer progression and the impact of subclonal mutations on tumor heterogeneity. The findings suggest that genome doubling may influence the selection of tumor suppressor inactivation events, and that subclonal mutations may play a key role in cancer development and response to therapy. The study provides a framework for further analysis of cancer genomes and their evolutionary trajectories.