Genome sequencing is positioned as a routine clinical work‐up for diverse clinical conditions. A commonly used approach to highlight candidate variants with potential clinical implication is to search over locus‐ and gene‐centric knowledge datab...
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https://www.riss.kr/link?id=O113106404
2020년
-
1059-7794
1098-1004
SCI;SCIE;SCOPUS
학술저널
387-396 [※수록면이 p5 이하이면, Review, Columns, Editor's Note, Abstract 등일 경우가 있습니다.]
0
상세조회0
다운로드다국어 초록 (Multilingual Abstract)
Genome sequencing is positioned as a routine clinical work‐up for diverse clinical conditions. A commonly used approach to highlight candidate variants with potential clinical implication is to search over locus‐ and gene‐centric knowledge datab...
Genome sequencing is positioned as a routine clinical work‐up for diverse clinical conditions. A commonly used approach to highlight candidate variants with potential clinical implication is to search over locus‐ and gene‐centric knowledge databases. Most web‐based applications allow a federated query across diverse databases for a single variant; however, sifting through a large number of genomic variants with combination of filtering criteria is a substantial challenge. Here we describe the Clinical Genome and Ancestry Report (CGAR), an interactive web application developed to follow clinical interpretation workflows by organizing variants into seven categories: (1) reported disease‐associated variants, (2) rare‐ and high‐impact variants in putative disease‐associated genes, (3) secondary findings that the American College of Medical Genetics and Genomics recommends reporting back to patients, (4) actionable pharmacogenomic variants, (5) focused reports for candidate genes, (6) de novo variant candidates for trio analysis, and (7) germline and somatic variants implicated in cancer risk, diagnosis, treatment and prognosis. For each variant, a comprehensive list of external links to variant‐centric and phenotype databases are provided. Furthermore, genotype‐derived ancestral composition is used to highlight allele frequencies from a matched population since some disease‐associated variants show a wide variation between populations. CGAR is an open‐source software and is available at https://tom.tch.harvard.edu/apps/cgar/.
Missense variants in TAF1 and developmental phenotypes: Challenges of determining pathogenicity