| Literature DB >> 23757202 |
Lora J H Bean1, Stuart W Tinker, Cristina da Silva, Madhuri R Hegde.
Abstract
Current technology allows clinical laboratories to rapidly translate research discoveries from small patient cohorts into clinical genetic tests; therefore, a potentially large proportion of sequence variants identified in individuals with clinical features of a genetic disorder remain unpublished. Without a mechanism for clinical laboratories to share data, interpretation of sequence variants may be inconsistent. We describe here the two components of Emory Genetics Laboratory's (EGL) in-house developed data management system. The first is a highly curated variant database with a data structure designed to facilitate sharing of information about variants identified at EGL with curated databases. This system also tracks changes in variant classifications, creating a record of previous cases in need of updated reports when a classification is changed. The second component, EmVClass, is a Web-based interface that allows any user to view the inventory of variants classified at EGL. These software tools provide a solution to two pressing issues faced by clinical genetics laboratories: how to manage a large variant inventory with evolving variant classifications that need to be communicated to healthcare providers and how to make that inventory of variants freely available to the community.Entities:
Keywords: bioinformatics; clinical genetics; mutation; mutation database; variant classification
Mesh:
Year: 2013 PMID: 23757202 DOI: 10.1002/humu.22364
Source DB: PubMed Journal: Hum Mutat ISSN: 1059-7794 Impact factor: 4.878