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For methods returning a false discovery rate, the proportion of highly expressed genes among all tested genes influences power after multiple testing correction.
“For methods that return a false discovery rate (FDR), the proportion of genes that are highly expressed out of the total set of genes being tested will also influence the power of detection after multiple testing correction [193].”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [193]
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Cites
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A survey of best practices for RNA-seq data analysis
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- Authors
- Noble, W. S.
- Affiliations
- University of Washington (US)
- Corresponding author
- Noble, William S
- ORCID
- Noble, William S
- Venue
- Nature Biotechnology
- Published
- 2009-12
- Volume
- 27
- Issue
- 12
- Pages
- 1135-1137
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC2907892
- OpenAlex
- W2002420618
- Cited by
- 772
- References
- 9
- Citations by year
- 2026: 58 · 2025: 58 · 2024: 82 · 2023: 45 · 2022: 56 · 2021: 76 · 2020: 64 · 2019: 60 · 2018: 55 · 2017: 58 · 2016: 42 · 2015: 34 · 2014: 21 · 2013: 22 · 2012: 24
- FWCI
- 5.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Center for Research Resources (P41RR0011823, P41RR011823)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- multiple testing correction, false positives, significance testing, high-throughput experimentation, hit prioritization, statistical analysis
- MeSH terms
- Algorithms, Data Interpretation, Statistical, Artifacts
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