Assessing effectiveness of many-objective evolutionary algorithms for selection of tag SNPs.

ABSTRACT:

Background

Studies on genome-wide associations help to determine the cause of many genetic diseases. Genome-wide associations typically focus on associations between single-nucleotide polymorphisms (SNPs). Genotyping every SNP in a chromosomal region for identifying genetic variation is computationally very expensive. A representative subset of SNPs, called tag SNPs, can be used to identify genetic variation. Small tag SNPs save the computation time of genotyping platform, however, there could be missing data or genotyping errors in small tag SNPs. This study aims to solve Tag SNPs selection problem using many-objective evolutionary algorithms.

Methods

Tag SNPs selection can be viewed as an optimization problem with some trade-offs between objectives, e.g. minimizing the num

SUBMITTER: Moqa R 

PROVIDER: S-EPMC9731481 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature