Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria Article Swipe
Related Concepts
Calibration
Univariate
Computational biology
Medicine
Psychology
Computer science
Biology
Machine learning
Statistics
Mathematics
Multivariate statistics
Timothy Bergquist
,
Sarah L. Stenton
,
Emily A.W. Nadeau
,
Alicia B. Byrne
,
Marc S. Greenblatt
,
Steven M. Harrison
,
Sean V. Tavtigian
,
Anne O’Donnell‐Luria
,
Leslie G. Biesecker
,
Predrag Radivojac
,
Steven E. Brenner
,
Vikas Pejaver
,
Leslie G. Biesecker
,
Steven M. Harrison
,
Ahmad Abou Tayoun
,
Jonathan S. Berg
,
Steven E. Brenner
,
Garry R. Cutting
,
Sian Ellard
,
Marc S. Greenblatt
,
Peter B. Kang
,
Izabela Karbassi
,
Rachel Karchin
,
Jessica L. Mester
,
Anne O’Donnell‐Luria
,
Tina Pesaran
,
Sharon E. Plon
,
Heidi L. Rehm
,
Natasha T. Strande
,
Sean V. Tavtigian
,
Scott Topper
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.gim.2025.101402
· OA: W4408278568
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.gim.2025.101402
· OA: W4408278568
At calibrated thresholds, 3 new computational predictors provided evidence for variant pathogenicity at similar strength to the 4 previously recommended predictors (and comparable with functional assays for some variants). This calibration broadens the scope of computational tools for application in clinical variant classification. Their new approaches offer promise for future advancement of the field.
Related Topics
Finding more related topics…