New guide to data interpretationJune 5, 2014 in Other Sciences / Mathematics
Western blotting is a widely used technique to detect specific proteins. Although considered a semi-quantitative method, the results are often interpreted quantitatively. Scientific articles often do not specify how researchers quantified these results and how they compared biological replicates for statistical testing.
Conway Fellow, Prof Boris Kholodenko and his team in Systems Biology Ireland have described how results of statistical testing applied to western blot data are affected by the choice of normalisation strategy applied to the data. They have created a step-by-step guide to help scientists choose the most appropriate normalisation strategy for their particular study.
Normalisation strategies transform or manipulate data to allow quantitative comparison of biological replicates. The Kholodenko group used mathematical models to simulate the effects of normalisation and actual experimental data to corroborate the results.
"We clarified the quantitative use of western blot data and how the normalisation strategy applied to the data affects the statistical testing, possibly increasing false positives or false negatives", explained Dr Andrea Degasperi from the Kholodenko group.
Western blotting provides experimental evidence that supports a given hypothesis and is also used to validate data obtained from other techniques. Clarifying its quantitative use for decision making or statistical testing is necessary.
The Kholodenko group hope their study findings will not only act as a reference for scientists but also encourage them to include this critical information about data interpretations in published articles.
A. Degasperi, M. R. Birtwistle, N. Volinsky, J. Rauch, W. Kolch, B. N. Kholodenko. "Evaluating Strategies to Normalise Biological Replicates of Western Blot Data." PLoS ONE, 9(1): e87293. DOI: 10.1371/journal.pone.0087293, 2014.
Provided by University College Dublin
"New guide to data interpretation" June 5, 2014 http://phys.org/news/2014-06-new-guide-to-data-interpretation.html