LEXINGTON, Ky. (Nov. 12, 2009) — Dave Fardo, assistant professor of biostatistics in the University of Kentucky College of Public Health, was recently published in PLoS Genetics. He and two co-authors developed a new quality control test statistic for family-based genome-wide association studies (GWAS).
"The standardized genome-wide transmission statistic allows us to look across a subject’s entire genome in order to assess the genotyping quality," said Fardo. "If we can figure out that a particular genetic location correlates to disease, then we can delve deeper into the reason for the differences in disease susceptibility."
A genome-wide association study is an approach that utilizes recently developed biological techniques that attempt to assay as much of the variable portion of the genome as possible, and recruits many people to find genetic variations associated with a particular disease. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease. Such studies are particularly useful in finding genetic variations that contribute to common, complex diseases, such as asthma, cancer, diabetes, heart disease and mental illnesses.
"What you want at the end of the day, after all the biological assays, is quality data that's representative of the actual genome," said Fardo. "If you're using data that is riddled with errors, then your inferences about the landscape of genetic susceptibility will be wrong. So this new method is another tool for ensuring data quality in a genome-wide association study."
This research was funded through National Heart Lung Blood Institute (NHLBI) grants.
"My hope is that this new test statistic will be utilized by the research community to improve data quality, thus, increasing the chance of finding true disease pre-disposing genetic loci," said Fardo.