The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Optimizing the noise versus bias trade-off for Illumina whole genome expression BeadChips
Open accessAbstract
Five strategies for pre-processing intensities from Illumina expression BeadChips are assessed from the point of view of precision and bias. The strategies include a popular variance stabilizing transformation and model-based background corrections that either use or ignore the control probes. Four calibration data sets are used to evaluate precision, bias and false discovery rate (FDR). The original algorithms are shown to have operating characteristics that are not easily comparable. Some tend to minimize noise while others minimize bias. Each original algorithm is shown to have an innate intensity offset, by which unlogged intensities are bounded away from zero, and the size of this offset determines its position on the noise-bias spectrum. By adding extra offsets, a continuum of related algorithms with different noise-bias trade-offs is generated, allowing direct comparison of the performance of the strategies on equivalent terms. Adding a positive offset is shown to decrease the FDR of each original algorithm. The potential of each strategy to generate an algorithm with an optimal noise-bias trade-off is explored by finding the offset that minimizes its FDR. The use of control probes as part of the background correction and normalization strategy is shown to achieve the lowest FDR for a given bias.
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“Offsets in a range of moderate values have been shown to achieve an effective compromise between noise and bias (24).”
From limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) · cites this paper as [24]
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Metadata
- Authors
- Shi, W., Oshlack, A., & Smyth, G. K.
- Affiliations
- The University of Melbourne (AU)
- Corresponding author
- Shi, Wei
- Smyth, Gordon K.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-10-06
- Volume
- 38
- Issue
- 22
- Pages
- e204-e204
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC3001098
- OpenAlex
- W2118373398
- Cited by
- 225
- References
- 32
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 8 · 2023: 10 · 2022: 13 · 2021: 15 · 2020: 11 · 2019: 20 · 2018: 14 · 2017: 19 · 2016: 28 · 2015: 23 · 2014: 15 · 2013: 20 · 2012: 9
- FWCI
- 5.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Medical Research Council
- National Health and Medical Research Council (490037)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- variance stabilizing transformation, background correction, false discovery rate, normalization, gene expression data
- MeSH terms
- Algorithms, Humans, Reproducibility of Results, Oligonucleotide Probes, Genome, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling
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