In the Eye of the Beholder: Does the Master See the SameSpots as the Novice?

Abstract

Historically, the use of two-dimensional electrophoresis (2-DE) in quantitative proteomics has been hampered by significant technical variance. Over the past decade, a range of technological leaps have reduced the overall variance of 2-DE, thus turning the technology into a robust platform for quantitative intact proteomics. However, as the confounding gel-to-gel variation improves, the variance arising from the subsequent image analysis becomes more prominent. Limitations in image alignment and spot detection of previous generations of 2-DE analysis software have demanded considerable user-intervention and manual editing, resulting in introduction of a large degree of subjectivity and software-induced variance. We evaluated the performance of SameSpots, representing a new generation of 2-DE image analysis software, using both DIGE and traditional single-stain 2-DE approaches. Evaluations of the software-induced variance in relation to other sources of variance, as well as the subjectivity through comparison of analyses performed by an expert user and a novice lab-user, were performed. In terms of statistical power, the less-experienced user achieved the better results, but no discernible difference was detected in multivariate comparisons between the users. In conclusion, we found that SameSpots represents improvements both in reproducibility and objectivity in relation to previous generations of 2-DE analysis software.