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The case for well-conducted experiments to validate statistical protocols for 2D gels: different pre-processing = different lists of significant proteins.

Sreelatha Meleth·Jessy Deshane·Helen Kim
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Abstract

BACKGROUND: The proteomics literature has seen a proliferation of publications that seek to apply the rapidly improving technology of 2D gels to study various biological systems. However, there is a dearth of systematic studies that have investigated appropriate statistical approaches to analyse the data from these experiments. RESULTS: Comparison of the effects of statistical pre-processing on the results of two sample t-tests suggests that the results of 2D gel experiments and by extension the conclusions derived from these experiments are not independent of the statistical protocol used. CONCLUSIONS: This study suggests that there is a need for well-conducted validation studies to establish optimal statistical techniques to be used on such data sets.

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AnimalsBiotechnologyBrainComputational BiologyData Interpretation, StatisticalDatabases, ProteinElectrophoresis, Gel, Two-DimensionalGene Expression ProfilingIsoelectric FocusingIsoelectric PointMass SpectrometryModels, StatisticalProteinsProteomeProteomicsRNARatsRats, Sprague-DawleyReproducibility of ResultsResearch DesignSoftwareJournal Article

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Sreelatha Meleth, Jessy Deshane, Helen Kim. 2005-02-11. The case for well-conducted experiments to validate statistical protocols for 2D gels: different pre-processing = different lists of significant proteins.. https://doi.org/10.1186/1472-6750-5-7

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