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ACMG Statements and Guidelines
These online statements and guidelines are definitive and may be cited using the digital object identifier (DOI). These recommendations are designed primarily as an educational resource for medical geneticists and other healthcare providers to help them provide quality medical genetics services; they should not be considered inclusive of all proper procedures and tests or exclusive of other procedures and tests that are reasonably directed to obtaining the same results. Please refer to the leading disclaimer in each document for more information.
2 Results
- ACMG Technical StandardOpen Archive
CFTR variant testing: a technical standard of the American College of Medical Genetics and Genomics (ACMG)
Genetics in MedicineVol. 22Issue 8p1288–1295Published in issue: August, 2020- Joshua L. Deignan
- Caroline Astbury
- Garry R. Cutting
- Daniela del Gaudio
- Anthony R. Gregg
- Wayne W. Grody
- and others
Cited in Scopus: 21Pathogenic variants in the CFTR gene are causative of classic cystic fibrosis (CF) as well as some nonclassic CF phenotypes. In 2001, CF became the first target of pan-ethnic universal carrier screening by molecular methods. The American College of Medical Genetics and Genomics (ACMG) recommended a core panel of 23 disease-causing variants as the minimal set to be included in pan-ethnic carrier screening of individuals with no family history of the disease, and these variants were usually assessed using targeted methods. - ACMG StatementOpen Archive
Points to consider in the reevaluation and reanalysis of genomic test results: a statement of the American College of Medical Genetics and Genomics (ACMG)
Genetics in MedicineVol. 21Issue 6p1267–1270Published in issue: June, 2019- Joshua L. Deignan
- Wendy K. Chung
- Hutton M. Kearney
- Kristin G. Monaghan
- Catherine W. Rehder
- Elizabeth C. Chao
- and others
Cited in Scopus: 79Reductions in the cost of genomic analyses and the elimination of gene patents for clinical diagnostics have enabled clinical laboratories to provide increasingly comprehensive genetic testing using sequencing, microarrays, and other methods, resulting in the generation of a vast amount of data that then needs to be analyzed.1 A significant challenge for clinical laboratory geneticists is the provision of accurate and consistent variant classification. Variant classification has historically been hindered by a lagging recognition of gene–disease associations, as well as a lack of publicly available data (including reference data) from clinical laboratories and other sources.
