Cancer Risk Score Prediction Based on a Single-Nucleotide Polymorphism Network.

ABSTRACT:

Objectives

Genome-wide association studies (GWAS) are performed to study the associations between genetic variants with respect to certain phenotypic traits such as cancer. However, the method that is commonly used in GWAS assumes that certain traits are solely affected by a single mutation. We propose a network analysis method, in which we generate association networks of single-nucleotide polymorphisms (SNPs) that can differentiate case and control groups. We hypothesize that certain phenotypic traits are attributable to mutations in groups of associated SNPs.

Methods

We propose a method based on a network analysis framework to study SNP-SNP interactions related to cancer incidence. We employed logistic regression to measure the significance of all SNP pairs from GWAS for

SUBMITTER: Mahesworo B 

PROVIDER: S-EPMC9388919 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature