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Operator- and software-related post-experimental variability and source of error in 2-DE analysis
Renato Millioni1, Lucia Puricelli, Stefano Sbrignadello
1Division of Metabolism, Department of Clinical and Experimental Medicine, University of Padua, via Giustiniani 2, 35128, Padua, Italy. millionirenato@gmail.com
Abstract:
In the field of proteomics, several approaches have been developed for separating proteins and analyzing their differential relative abundance. One of the oldest, yet still widely used, is 2-DE. Despite the continuous advance of new methods, which are less demanding from a technical standpoint, 2-DE is still compelling and has a lot of potential for improvement. The overall variability which affects 2-DE includes biological, experimental, and post-experimental (software-related) variance. It is important to highlight how much of the total variability of this technique is due to post-experimental variability, which, so far, has been largely neglected. In this short review, we have focused on this topic and explained that post-experimental variability and source of error can be further divided into those which are software-dependent and those which are operator-dependent. We discuss these issues in detail, offering suggestions for reducing errors that may affect the quality of results, summarizing the advantages and drawbacks of each approach.
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