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PATH-SCAN: a reporting tool for identifying clinically actionable variants.
Daneshjou, Roxana; Zappala, Zachary; Kukurba, Kim; Boyle, Sean M; Ormond, Kelly E; Klein, Teri E; Snyder, Michael; Bustamante, Carlos D; Altman, Russ B; Montgomery, Stephen B.
Affiliation
  • Daneshjou R; Department of Genetics, Stanford University, Stanford, CA 94061, United States.
Pac Symp Biocomput ; : 229-40, 2014.
Article in En | MEDLINE | ID: mdl-24297550
ABSTRACT
The American College of Medical Genetics and Genomics (ACMG) recently released guidelines regarding the reporting of incidental findings in sequencing data. Given the availability of Direct to Consumer (DTC) genetic testing and the falling cost of whole exome and genome sequencing, individuals will increasingly have the opportunity to analyze their own genomic data. We have developed a web-based tool, PATH-SCAN, which annotates individual genomes and exomes for ClinVar designated pathogenic variants found within the genes from the ACMG guidelines. Because mutations in these genes predispose individuals to conditions with actionable outcomes, our tool will allow individuals or researchers to identify potential risk variants in order to consult physicians or genetic counselors for further evaluation. Moreover, our tool allows individuals to anonymously submit their pathogenic burden, so that we can crowd source the collection of quantitative information regarding the frequency of these variants. We tested our tool on 1092 publicly available genomes from the 1000 Genomes project, 163 genomes from the Personal Genome Project, and 15 genomes from a clinical genome sequencing research project. Excluding the most commonly seen variant in 1000 Genomes, about 20% of all genomes analyzed had a ClinVar designated pathogenic variant that required further evaluation.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Variation / Software / Genetic Testing Type of study: Diagnostic_studies / Guideline / Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Journal: Pac Symp Biocomput Journal subject: BIOTECNOLOGIA / INFORMATICA MEDICA Year: 2014 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Variation / Software / Genetic Testing Type of study: Diagnostic_studies / Guideline / Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Journal: Pac Symp Biocomput Journal subject: BIOTECNOLOGIA / INFORMATICA MEDICA Year: 2014 Type: Article Affiliation country: United States