Posters
A Consensus-Based Machine Learning Framework to Determine Genetically Inferred Ancestry (GIA) from Comprehensive Genomic Profiling (CGP) Sequencing Results
17 Nov 2023
This study developed and validated a workflow for accurately determining the genetically inferred ancestry (GIA) of patients from comprehensive genomic profiling (CGP) sequencing results, which can enable ancestry-aware biomarker research and contribute to reducing cancer disparities and improving representation in clinical trials.
- Zachary D. Wallen
- Mary K. Nesline
- Sarabjot Pabla
- Shuang Gao
- Erik Van Roey
- Stephanie B. Hastings
- Kyle C. Strickland
- Rebecca A. Previs
- Shengle Zhang
- Jeffrey M. Conroy
- Taylor J. Jensen
- Elizabeth George
- Marcia Eisenberg
- Brian Caveney
- Pratheesh Sathyan
- Prasanth Reddy
- Eric A. Severson
- Shakti Ramkissoon