Journal
PROTEOMICS
Volume 11, Issue 6, Pages 1037-1048Publisher
WILEY
DOI: 10.1002/pmic.201000579
Keywords
Bioinformatics; Components of variance; Experimental design; Quality control; Randomization; Sample size
Funding
- UK Medical Research Council [G0802416]
- Cancer Research UK
- Medical Research Council [G0802416] Funding Source: researchfish
- MRC [G0802416] Funding Source: UKRI
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Quality control is becoming increasingly important in proteomic investigations as experiments become more multivariate and quantitative. Quality control applies to all stages of an investigation and statistics can play a key role. In this review, the role of statistical ideas in the design and planning of an investigation is described. This involves the design of unbiased experiments using key concepts from statistical experimental design, the understanding of the biological and analytical variation in a system using variance components analysis and the determination of a required sample size to perform a statistically powerful investigation. These concepts are described through simple examples and an example data set from a 2-D DIGE pilot experiment. Each of these concepts can prove useful in producing better and more reproducible data.
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