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 |
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MDPI AG
2024-03-01
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| Series: | Genes |
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| Online Access: | https://www.mdpi.com/2073-4425/15/3/344 |
| _version_ | 1797240871404437504 |
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| author | Yonghui Ni Anna Eames Seffernick Arzu Onar-Thomas Stanley B. Pounds |
| author_facet | Yonghui Ni Anna Eames Seffernick Arzu Onar-Thomas Stanley B. Pounds |
| author_sort | Yonghui Ni |
| collection | DOAJ |
| description | 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-rectangle approximation of a <i>p</i>-value histogram to derive a formula to compute the statistical power and sample size for analyses that involve the FDR. We also introduce the R package <i>FDRsamplesize2</i>, which incorporates these and other power calculation formulas to compute power for a broad variety of studies not covered by other FDR power calculation software. A few illustrative examples are provided. The <i>FDRsamplesize2</i> package is available on CRAN. |
| first_indexed | 2024-04-24T18:14:19Z |
| format | Article |
| id | doaj.art-298b4d368a384ca1b6cce69fe8aa8fe3 |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-04-24T18:14:19Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-298b4d368a384ca1b6cce69fe8aa8fe32024-03-27T13:43:08ZengMDPI AGGenes2073-44252024-03-0115334410.3390/genes15030344Computing Power and Sample Size for the False Discovery Rate in Multiple ApplicationsYonghui Ni0Anna Eames Seffernick1Arzu Onar-Thomas2Stanley B. Pounds3Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USADepartment of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USADepartment of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USADepartment of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USAThe 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-rectangle approximation of a <i>p</i>-value histogram to derive a formula to compute the statistical power and sample size for analyses that involve the FDR. We also introduce the R package <i>FDRsamplesize2</i>, which incorporates these and other power calculation formulas to compute power for a broad variety of studies not covered by other FDR power calculation software. A few illustrative examples are provided. The <i>FDRsamplesize2</i> package is available on CRAN.https://www.mdpi.com/2073-4425/15/3/344false discovery ratepowersample sizemultiple testingproportion of true null hypotheses |
| spellingShingle | Yonghui Ni Anna Eames Seffernick Arzu Onar-Thomas Stanley B. Pounds Computing Power and Sample Size for the False Discovery Rate in Multiple Applications Genes false discovery rate power sample size multiple testing proportion of true null hypotheses |
| title | Computing Power and Sample Size for the False Discovery Rate in Multiple Applications |
| title_full | Computing Power and Sample Size for the False Discovery Rate in Multiple Applications |
| title_fullStr | Computing Power and Sample Size for the False Discovery Rate in Multiple Applications |
| title_full_unstemmed | Computing Power and Sample Size for the False Discovery Rate in Multiple Applications |
| title_short | Computing Power and Sample Size for the False Discovery Rate in Multiple Applications |
| title_sort | computing power and sample size for the false discovery rate in multiple applications |
| topic | false discovery rate power sample size multiple testing proportion of true null hypotheses |
| url | https://www.mdpi.com/2073-4425/15/3/344 |
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