Question

When identifying SNPs associated with disease susceptibility, what statistical threshold is standardly required to account for multiple hypothesis testing in genome-wide association studies?

Accepted Answer

The standard statistical threshold required to account for multiple hypothesis testing in genome-wide association studies is a p-value of 5 times 10 to the power of negative 8. A genome-wide association study involves testing hundreds of thousands or millions of single nucleotide polymorphisms, which are specific variations at single positions in a DNA sequence, to determine if they occur more frequently in people with a disease than in healthy individuals. Because researchers perform so many individual statistical tests simultaneously, there is a high probability of finding a significant result purely by chance, a phenomenon known as a false positive. To control for this, scientists apply the Bonferroni correction, which is a mathematical adjustment that requires a much stricter significance level to ensure the results are likely real. The threshold of 5 times 10 to the power of negative 8 is derived from the estimated number of independent blocks of genetic information in the human genome, roughly one million, divided into a standard significance level of 0.05. This specific p-value threshold ensures that the expected number of false positives across the entire genome remains extremely low, typically less than one, providing high confidence that any identified genetic marker is genuinely associated with the trait being studied.

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When identifying SNPs associated with disease susceptibility, what statistical threshold is standardly required to account for multiple hypothesis testing in genome-wide association studies?