In This Issue
A Disruptive Paradigm of Genetic Data Sharing and Analysis
Article first published online: 14 AUG 2013
© 2013 WILEY PERIODICALS, INC.
Volume 34, Issue 9, page iv, September 2013
How to Cite
Cotton, R. (2013), A Disruptive Paradigm of Genetic Data Sharing and Analysis. Hum. Mutat., 34: iv. doi: 10.1002/humu.22195
- Issue published online: 14 AUG 2013
- Article first published online: 14 AUG 2013
There are currently three critical major silos of activity in genetics and genomics: clinical genetics; GWAS/association/linkage; and the recent ‘new disease gene’ area. The latter two are in the research arena and as such have been relatively well funded and data are shared, especially in the GWAS field. The genetic health care of those with known genetic disease is in the public health arena. Optimum health care ideally involves instant access to data on all instances of the genetic variation of the patient in front of the clinician, so that state-of-the-art diagnosis, prognosis and treatment can be administered.
Bean et al. (Hum Mutat 34:1183-1188, 2013) have brought this ideal closer. Researchers at the Emory University Genetics Laboratory (EGL) have developed a data management system for genetic variations causing disease that was made public in an unprecedented way. EmVClass is a web-based interface allowing the viewers to access the inventory of classified variants in what is a sizeable genetic diagnostics lab. It is not a universal database and it contains only changes seen in genes tested at EGL, but it capitalizes on an infrastructure designed to facilitate submission to larger databases such as LOVD and ClinVar. EmVClass also facilitates scanning the EGL database for patients who have been reported with a reclassified variant and issues revised reports as well as allows clients to request revised reports. Appropriate patient privacy is maintained.
If all laboratories were to follow this example, patients with inherited disease could have care based on maximal information, especially if software was available to easily ‘trawl’ the data from other labs. Thus the problems of unpublished variants and completeness of highly curated gene-specific databases would be overcome and we would move more quickly to a complete catalogue of all variants in the human genome.