Importance of Block Randomization When Designing Proteomics Experiments
Bram Burger, Marc Vaudel, Harald Barsnes
Abstract
Randomization is used in experimental design to reduce the prevalence of unanticipated confounders. Complete randomization can however create imbalanced designs, for example, grouping all samples of the same condition in the same batch. Block randomization is an approach that can prevent severe imbalances in sample allocation with respect to both known and unknown confounders. This feature provides the reader with an introduction to blocking and randomization, and insights into how to effectively organize samples during experimental design, with special considerations with respect to proteomics.
Topics & Concepts
RandomizationConfoundingComputer scienceSample size determinationBlocking (statistics)Design of experimentsMendelian randomizationRestricted randomizationBlock (permutation group theory)ProteomicsResearch designData miningStatisticsClinical trialBioinformaticsMathematicsBiologyGenotypeGenetic variantsComputer networkBiochemistryGeneGeometryStatistical Methods in Clinical TrialsAdvanced Proteomics Techniques and ApplicationsGene expression and cancer classification