| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1166295 | Analytica Chimica Acta | 2012 | 7 Pages |
Spot detection is a mandatory step in all available software packages dedicated to the analysis of 2D gel images. As the majority of spots do not represent individual proteins, spot detection can obscure the results of data analysis significantly. This problem can be overcome by a pixel-level analysis of 2D images.Differences between the spot and the pixel-level approaches are demonstrated by variance analysis for real data sets (part of a larger research project initiated to investigate the molecular mechanism of the response of the potato to drought stress). As the method of choice for the analysis of data variation, the non-parametric MANOVA was chosen. NP-MANOVA is recommended as a flexible and very fast tool for the evaluation of the statistical significance of the factor(s) studied.
Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Spot detection is a serious bottleneck of analysis of 2D-electropherograms. ► Comparison of variance analysis performed for the spot and the pixel level. ► The non-parametric MANOVA is recommended as a flexible and very fast method.
