Based on these preliminary results, we suggest that the PST can be a model of organization that is effective and efficient in improving the psycho-social and spiritual aspects of care of terminally ill patients. Further follow-up and evaluation with validated tools are the main goals for the immediate future.

Motivation Germline variant classification allows accurate genetic diagnosis and risk assessment. However, it is a tedious iterative process integrating information from several sources and types of evidence. It should follow gene-specific (if available) or general updated international guidelines. Thus, it is the main burden of the incorporation of NGS into the clinical setting. Results We created the vaRHC R package to assist the process of variant classification in hereditary cancer by : 1) collecting information from diverse databases; 2) assigning or denying different types of evidence according to updated ACMG/AMP gene-specific criteria for ATM, CDH1, CHEK2, MLH1, MSH2, MSH6, PMS2, PTEN, and TP53 and general criteria for other genes; 3) providing an automated classification of variants using a Bayesian metastructure and considering CanVIG-UK recommendations; 4) optionally printing the output to an .xlsx file. A validation using 659 classified variants demonstrated the robustness of vaRHC, presenting a better criteria assignment than Cancer SIGVAR, an available similar tool. Availability The source code can be consulted in the GitHub repository (https://github.com/emunte/vaRHC) Additionally, it will be submitted to CRAN soon. Supplementary information Supplementary data are available at Bioinformatics online.