A knowledge-based framework for the discovery of cancer-predisposing variants using large-scale sequencing breast cancer data.

ABSTRACT:

Background

The landscape of cancer-predisposing genes has been extensively investigated in the last 30 years with various methodologies ranging from candidate gene to genome-wide association studies. However, sequencing data are still poorly exploited in cancer predisposition studies due to the lack of statistical power when comparing millions of variants at once.

Method

To overcome these power limitations, we propose a knowledge-based framework founded on the characteristics of known cancer-predisposing variants and genes. Under our framework, we took advantage of a combination of previously generated datasets of sequencing experiments to identify novel breast cancer-predisposing variants, comparing the normal genomes of 673 breast cancer patients of European origin against

SUBMITTER: Melloni GEM 

PROVIDER: S-EPMC5452392 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature