Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations

Abstract excerpt

BACKGROUND: Massively parallel sequencing studies have led to the identification of a large number of mutations present in a minority of cancers of a given site. Hence, methods to identify the likely pathogenic mutations that are worth exploring experimentally and clinically are required. We sought to compare the performance of 15 mutation effect prediction algorithms and their agreement. As a...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Cancer Genomics and Diagnostics
• Share to Genetic factors in colorectal cancer
• Share to Genomics and Rare Diseases