Abstract
The statistical design of a clinical proteomics experiment is a critical part of well-undertaken investigation. Standard concepts from experimental design such as randomization, replication and blocking should be applied in all experiments, and this is possible when the experimental conditions are well understood by the investigator. The large number of proteins simultaneously considered in proteomic discovery experiments means that determining the number of required replicates to perform a powerful experiment is more complicated than in simple experiments. However, by using information about the nature of an experiment and making simple assumptions this is achievable for a variety of experiments useful for biomarker discovery and initial validation.
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Acknowledgment
This work was supported by a Career Development Award from the UK Medical Research Council [G0802416].
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Cairns, D.A. (2015). Statistical Issues in the Design and Planning of Proteomic Profiling Experiments. In: Vlahou, A., Makridakis, M. (eds) Clinical Proteomics. Methods in Molecular Biology, vol 1243. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1872-0_13
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DOI: https://doi.org/10.1007/978-1-4939-1872-0_13
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