All-FIT: allele-frequency-based imputation of tumor purity from high-depth sequencing data.

SUMMARY: Clinical sequencing aims to identify somatic mutations in cancer cells for accurate diagnosis and treatment. However, most widely used clinical assays lack patient-matched control DNA and additional analysis is needed to distinguish somatic and unfiltered germline variants. Such computational analyses require accurate assessment of tumor cell content in individual specimens. Histological estimates often do not corroborate with results from computational methods that are primarily designed for normal-tumor matched data and can be confounded by genomic heterogeneity and presence of sub-clonal mutations. Allele-frequency-based imputation of tumor (All-FIT) is an iterative weighted least square method to estimate specimen tumor purity based on the allele frequencies of variants detected in high-depth, targeted, clinical sequencing data. Using simulated and clinical data, we demonstrate All-FIT's accuracy and improved performance against leading computational approaches, highlighting the importance of interpreting purity estimates based on expected biology of tumors. AVAILABILITY AND IMPLEMENTATION: Freely available at http://software.khiabanian-lab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hepatitis Outreach Network: a practical strategy for hepatitis screening with linkage to care in foreign-born communities.

BACKGROUND & AIMS: Many foreign-born persons in the US are at high risk of chronic hepatitis B (HBV) and C (HCV) infections, yet are not aware of their infection, and lack healthcare coverage or linkage to care. METHODS: A unique partnership, the Hepatitis Outreach Network, combines the expertise and resources of the Mount Sinai School of Medicine, the NYC Department of Health and Mental Hygiene, and community-based organizations, to provide education, screening and link to care in communities with high prevalence of chronic viral hepatitis. Comprehensive HBV and HCV screening identifies infected patients, who then receive further evaluation from either local or Mount Sinai physicians, combined with patient-navigators who organize follow-up visits. RESULTS: Of 1603 persons screened, 76 had HBV and 75 had HCV. Importantly, screening for HCV based on traditional risk factors would have missed 67% of those who tested positive. Of the 76 persons with HCV infection, 49 (64%) received a medical evaluation (26 with local providers and 23 at Mount Sinai). Of the 49 HCV-infected persons evaluated, treatment was recommended in 11 and begun in 8 (73%). Of the 76 persons with HBV infection, 43 (57%) received a medical evaluation (31 with local providers and 12 at Mount Sinai). Of the 43 HBV-infected persons evaluated, treatment was recommended and begun in 5 (100%). CONCLUSIONS: Hepatitis Outreach Network has successfully established novel proof of concept for identifying HBV and HCV infections in foreign-born persons through use of several unique elements that effectively link them to care.