The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Statistical design and the analysis of gene expression microarray data
Open accessAbstract
Gene expression microarrays are an innovative technology with enormous promise to help geneticists explore and understand the genome. Although the potential of this technology has been clearly demonstrated, many important and interesting statistical questions persist. We relate certain features of microarrays to other kinds of experimental data and argue that classical statistical techniques are appropriate and useful. We advocate greater attention to experimental design issues and a more prominent role for the ideas of statistical inference in microarray studies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Cited by
Fundamentals of experimental design for cDNA microarrays
Churchill, G. A. (2002) · Nature Genetics · doi:10.1038/ng1031 · Cited by 1,050
Self-citationVariation in gene expression within and among natural populations
Oleksiak, M. F., Churchill, G. A., & Crawford, D. L. (2002) · Nature Genetics · doi:10.1038/ng983 · Cited by 736
Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments
Kerr, M. K., & Churchill, G. A. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.161273698 · Cited by 474
Self-citationTranscriptional outputs of the Caenorhabditis elegans forkhead protein DAF‐16
McElwee, J., Bubb, K., & Thomas, J. H. (2003) · Aging Cell · doi:10.1046/j.1474-9728.2003.00043.x · Cited by 416
Statistical Design and Analysis of RNA Sequencing Data
Auer, P. L., & Doerge, R. W. (2010) · Genetics · doi:10.1534/genetics.110.114983 · Cited by 393
Metadata
- Authors
- KERR, M. K., & CHURCHILL, G. A.
- Venue
- Genetics Research
- Publisher
- Hindawi Limited
- Published
- 2007-12
- Volume
- 89
- Issue
- 5-6
- Pages
- 509-514
- ISSN
- 0016-6723 (ISSN-L)
- 1469-5073
- OpenAlex
- W2096758922
- Cited by
- 560
- References
- 1
- FWCI
- 14.25
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Statistical design and the analysis of gene expression microarray data. https://app.cochat.ai/papers/10.1017/s0016672308009713
- The paper
- KERR, M. K., & CHURCHILL, G. A. (2007). Statistical design and the analysis of gene expression microarray data. Genetics Research. https://doi.org/10.1017/s0016672308009713
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
