Recognition and management of individuals susceptible to disease are critical for patient care. However, identification of these patients is very challenging, especially in oncology. Dr. Peter Park and his group at the Department of Biomedical Informatics, Harvard Medical School have developed a bioinformatics platform enabling identification of patients predisposed to cancer by analyzing DNA copy number variation (CNV) in peripheral blood samples. BIC-seq2 algorithms developed by Dr. Park enable accurate and unbiased identification of known and novel disease predisposing CNVs, and can facilitate accurate detection of both somatic and germline variants in liquid biopsies. The method combines normalization of whole-genome sequencing data and Bayesian information criterion-based segmentation to identify CNVs linked to disease susceptibility. This platform described in a recent paper was originally utilized for identification of known and novel cancer predisposing CNVs. We believe this platform could be used to guide early cancer detection and potentially identification of novel targets in drug discovery programs in oncology and other disease areas.