Related Experiment Video
Updated: Jun 3, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Application of the optimal discovery procedure to genetic case-control studies: comparison with p values and
Ioanna Tachmazidou1, Maria De Iorio, Frank Dudbridge
1Medical Research Council, Biostatistics Unit, Institute of Public Health, Cambridge, UK. ioanna.tachmazidou@mrc-bsu.cam.ac.uk
Objectives:
The power of genetic association studies is limited by stringent levels of statistical significance. To improve power, Bayes factors (BFs) have been suggested as an alternative measure to the p value, and Storey recently introduced an optimal discovery procedure (ODP) for multiple testing. We aimed to adapt the ODP to genetic case-control studies and to compare its power to p values and asymptotic BFs (ABFs).
Methods:
We propose estimators of the ODP based on prospective and retrospective likelihoods. We performed simulations based on independent common SNPs and on sequence data including rare variants. Effects of causal SNPs were simulated under various distributions of effect size.
Results:
The true ODP is never outperformed, but the estimated ODP has similar power to p values and ABFs. For common SNPs the ODP offers power advantages only in extreme scenarios. However, for rare variants the ODP and ABF detect more associations at low false-positive rates than do p values.
Conclusions:
The ODP can provide higher power than p values for genetic case-control studies of common variants. However, as the ABF has similar power to the ODP and is computed more rapidly, it is our currently preferred method.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
P-value
P-value stands for the probability value. P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more unlikely...
Probability Laws

