Statistical methods for analysis of high-throughput RNA interference screens
Open accessAbstract
RNA interference (RNAi) has become a powerful technique for reverse genetics and drug discovery, and in both of these areas large-scale high-throughput RNAi screens are commonly performed. The statistical techniques used to analyze these screens are frequently borrowed directly from small-molecule screening; however, small-molecule and RNAi data characteristics differ in meaningful ways. We examine the similarities and differences between RNAi and small-molecule screens, highlighting particular characteristics of RNAi screen data that must be addressed during analysis. Additionally, we provide guidance on selection of analysis techniques in the context of a sample workflow.
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The robust Z-score is sensitive to shifts in median and commonly used as a normalization and strength of perturbation value in image-based phenotypic profiling, but it has not been used for estimating replicate dissimilarity nor compared to other distance metrics.
“The robust Z-score is sensitive to shifts in median, and commonly used as a normalization and strength of perturbation value in the context of image-based phenotypic profiling, but it has not been used for estimating replicate dissimilarity, nor compared to other distance metrics12,30,37.”
From A statistical framework for high-content phenotypic profiling using cellular feature distributions (2022) · cites this paper as [37]
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“The robust Z-score is sensitive to shifts in median, and commonly used as a normalization and strength of perturbation value in the context of image-based phenotypic pro fi ling, but it has not been used for estimating replicate dissimilarity, nor compared to other distance metrics 12,30,37 .”
- Authors
- Birmingham, A., Selfors, L. M., Forster, T., Wrobel, D., Kennedy, C. J., Shanks, E., Santoyo-Lopez, J., Dunican, D. J., Long, A., Kelleher, D., Smith, Q., Beijersbergen, R. L., Ghazal, P., & Shamu, C. E.
- Affiliations
- Harvard University (US)
- University of Edinburgh (GB)
- University of Dundee (GB)
- Trinity College Dublin (IE)
- Thermo Fisher Scientific (United States) (US)
- The Netherlands Cancer Institute (NL)
- Corresponding author
- Birmingham, Amanda
- ORCID
- Venue
- Nature Methods
- Published
- 2009-07-30
- Volume
- 6
- Issue
- 8
- Pages
- 569-575
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC2789971
- OpenAlex
- W2150091347
- Cited by
- 586
- References
- 37
- Citations by year
- 2026: 9 · 2025: 15 · 2024: 15 · 2023: 21 · 2022: 30 · 2021: 29 · 2020: 44 · 2019: 35 · 2018: 39 · 2017: 46 · 2016: 48 · 2015: 50 · 2014: 57 · 2013: 45 · 2012: 38
- FWCI
- 2.63
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Funders
- Wellcome Trust
- European Commission
- National Institutes of Health (AI057159)
- Directorate for Biological Sciences
- Engineering and Physical Sciences Research Council
- Biotechnology and Biological Sciences Research Council (D019621, BB/D019621/1)
- National Cancer Institute (P01CA078048, CA078048)
- National Institute of Allergy and Infectious Diseases (AI 067751, U19AI067751, AI057159, U54AI057159)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- RNAi screen, high-throughput screening, reverse genetics, drug discovery, analysis workflows
- MeSH terms
- Animals, Computer Simulation, Research Design, Models, Statistical, RNA Interference, RNA, Small Interfering, Small Molecule Libraries
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