Geometrical distortions in two-dimensional gels: applicable correction methods

Two-dimensional electrophoresis (2-DE) provides a rapid means for separating thousands of proteins from cell and tissue samples in one run. Although this powerful research tool has been enthusiastically applied in many fields of biomedical research, accurate analysis and interpretation of the data have provided many challenges. Several analysis steps are needed to convert the large amount of noisy data obtained with 2-DE into reliable and interpretable biological information. The goals of such analysis steps include accurate protein detection and quantification, as well as the identification of differentially expressed proteins between samples run on different gels. To achieve these goals, systematic errors such as geometric distortions between the gels must be corrected by using computer-assisted methods. A wide range of computer software has been developed, but no general consensus exists as standard for 2-DE data analysis protocol. The choice of analysis approach is an important element depending both on the data and on the goals of the experiment. Therefore, basic understanding of the algorithms behind the software is required for optimal results. This review highlights some of the common themes in 2-DE data analysis, including protein spot detection and geometric image warping using both spot- and pixel-based approaches. Several computational strategies are overviewed and their relative merits and potential pitfalls discussed. Finally, we offer our own personal view of future trends and developments in large-scale proteome research.