The characterization of somatic mutations through genome sequencing of tumours has revolutionized cancer research, playing a crucial role in understanding tumorigenesis, tumour heterogeneity and identifying candidate actionable targets. In our research we use long and short read sequence data to identify germline and somatic variants linked to tumour development and mutational events driving tumor development. This talk will describe a study where we sought to investigate if the integration of homologous recombination deficiency (HRD) status can aid the prediction of pathogenicity for germline BRCA1 and BRCA2 variants. We analysed breast tumour whole-genome sequence and matching germline data from 350 patients across four datasets. Germline variants in BRCA1, BRCA2, and other DNA repair genes (PALB2, BARD1, BRIP1, RAD51C, RAD51D, CHEK2, ATM) were curated and patients with significant germline variants or variants of uncertain significance in these genes identified. Somatic HRD status was predicted using three previously reported algorithms: HRDetect, CHORD, and HRDSum. As expected HR-deficient and HR-proficient status were significant predictors of germline variant classification in both pathogenic and benign directions. Using specific signatures of BRCA1 and BRCA2 assigned by CHORD added precision to the classification of variants. We applied this approach to variants of uncertain significance in BRCA1 and BRCA2, to assist with future classification of these variants. This analysis highlighted that HRD status prediction algorithms provide valuable evidence to aid in the classification of germline BRCA1 and BRCA2 variants, offering a promising strategy for reducing the uncertainty in variant interpretation.