Candidate Single Nucleotide Polymorphism Selection using Publicly Available Tools: A Guide for Epidemiologists

摘要: Single nucleotide polymorphisms (SNPs) are the most common form of human genetic variation, with millions present in genome. Because only 1% might be expected to confer more than modest individual effects association studies, selection predictive candidate variants for complex disease analyses is formidable. Technologic advances SNP discovery and ever-changing annotation genome have led massive informational resources that can difficult master across disciplines. A simplified guide needed. Although methods evaluating nonsynonymous coding SNPs known, several other publicly available computational tools utilized assess polymorphic noncoding regions. As an example, authors applied multiple select DNA double-strand break repair genes. They chose evaluate occurred among a preexisting set 57 validated assays justify new assay development 83 potential DNA-dependent protein kinase catalytic subunit. Of 140 SNPs, eliminated 119 low or neutral predictions. The existing they used semiquantitative relative ranking strategy developed adapted priori post hoc evaluation identified whole scans within haplotype blocks associated disease. show ‘‘real world’’ application some bioinformatics use large epidemiologic studies analyses. also reviewed alternative approaches provide related information. amino acid sequence; base methods; predisposition disease; polymorphism, single