Computing Power and Sample Size for the False Discovery Rate in Multiple Applications
The false discovery rate (FDR) is a widely used metric of statistical significance for genomic data analyses that involve multiple hypothesis testing. Power and sample size considerations are important in planning studies that perform these types of genomic data analyses. Here, we propose a three-re...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-03-01
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| Series: | Genes |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4425/15/3/344 |