Sample interview questions: Can you explain the concept of false discovery rate and its application in epigenetics research?
Sample answer:
Concept of False Discovery Rate (FDR)
In statistical analysis, FDR refers to the expected proportion of false positives among the rejected null hypotheses. FDR controls the probability of making Type I errors (false positives) across multiple hypothesis tests.
Application in Epigenetics Research
Epigenetic studies often involve analyzing large datasets with many hypothesis tests, increasing the chances of false positives. To control this, FDR is employed:
- Identify differentially methylated regions (DMRs): FDR helps identify DMRs that are significantly different between case and control groups, minimizing false discovery of non-significant regions.
- Detect differentially expressed genes: FDR can be used to identify genes with significant differences in expression levels, accounting for multiple tests and controlling for false positives.
- Network analysis: FDR assists in constructing epigenetic networks by identifying significant interactions between epigenetic marks and genes, reducing the likelihood of spurious connections.
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