Approaches to Classification of Variants in TP53 and Other Hereditary Cancer Genes - Ambry Genetics
Offered By: Ambry Genetics via YouTube
Course Description
Overview
Syllabus
Intro
Reminders
Logistics
Background - my variant classification activities
Overview
ACMG weighted qualitative classification system
Quantitative evidence: multifactorial likelihood analysis
Clinically calibrated bioinformatic information? Assess bioinformatic features of proven pathogenic and non-pathogenic variants in large datasets -Determine the proportion of pathogenic variants in a given bioinformatogroup
Segregation data
Other components of the model?
Alignment to ACMG codes?
Recent examples of calibration
BRCA1/2 functional assay calibration
Estimating Functional Assay LRs
BRCA1/2 splicing assay calibration
Strength of evidence for splicing data
Population allele frequency as a predictor
Strength of evidence for population frequency
TP53 ACMG code strengths - starting from scratch
Converting bioinformatic predictions to ACMG/AMP
Comparing tool performance
Comparing performance for tools in combination
Specifying PM5 ACMGIAMP rule for TP53
Using somatic data - somatic to germline ratio
Using somatic data - Second hit
Conclusions
Acknowledgements for work presented here
Taught by
Ambry Genetics
Related Courses
Introduction to Data ScienceUniversity of Washington via Coursera Big Data Analytics in Healthcare
Georgia Institute of Technology via Udacity More Data Mining with Weka
University of Waikato via Independent Mining Massive Datasets
Stanford University via edX Pattern Discovery in Data Mining
University of Illinois at Urbana-Champaign via Coursera