variant classification

Invitae sees Jungla's AI platform as complementary to its own variant classification and interpretation methods.

Researchers tracked down monogenic risk variants, carriers, disease culprits, and more for 50 individuals with cardiomyopathy and 50 unaffected participants.

Investigators used gene panel sequence data to look at rare de novo variant frequencies in potential risk genes for neurodevelopmental disorders with epilepsy.

With machine learning and clinical natural language processing, the team has come up with more automated methods to do provisional diagnoses on children with genetic disease.

Researchers classified 64 hereditary cancer gene variants with RNA genetic test data, investigating related management changes and potential impacts in other DNA test recipients.

Researchers were able to classify 1,244 of 4,585 putatively clinically relevant rare variants genotyped on the UKB microarray as high quality.

Researchers used exome data for more than 123,000 individuals to map "constrained coding regions," where disease-related variants are over-represented.

Genetic counselors, laboratories, and patients themselves have roles to play in reclassifying gene variants, including variants of uncertain significance.