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The state of the art in the analysis of two-dimensional gel electrophoresis images.

Berth M, Moser FM, Kolbe M, Bernhardt J - Appl. Microbiol. Biotechnol. (2007)

Bottom Line: Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments.Challenges for analysis software as well as good practices are highlighted.We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

View Article: PubMed Central - PubMed

Affiliation: DECODON GmbH, Rathenau-Strasse 49a, 17489 Greifswald, Germany.

ABSTRACT
Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

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Example of a gray level calibration curve that is used in special image file formats. Gray levels found in the image file have to be interpreted according to the curve before being summed up for quantitation. The curve has lower slope in the low intensity range resulting in better quantitative resolution for weak signals
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Fig10: Example of a gray level calibration curve that is used in special image file formats. Gray levels found in the image file have to be interpreted according to the curve before being summed up for quantitation. The curve has lower slope in the low intensity range resulting in better quantitative resolution for weak signals

Mentions: Calibration inherent in the file format (Fig. 10). Some imaging devices can measure more intensity values than what fit into the available image file formats. For example, if the imaging device can measure a range of 120,000 intensity values, this range cannot be stored into a 16-bit TIFF image because the file format only provides 65,536 possible gray levels per pixel. One way to deal with this is to transform the measured intensity values linearly into the range of gray levels in the image file. Alternatively, because, for lower signal intensities, higher accuracy is desirable, a nonlinear function (e.g., square root transform as illustrated in Fig. 10) is applied by some imaging devices. This provides a more precise representation of lower-intensity pixels at the price of lower accuracy for high intensities. The corresponding vendor-specific file formats, e.g., Fuji’s IMG/INF format (Fujifilm, Düsseldorf, Germany) and the GEL format used in devices by Molecular Dynamics (Sunnyvale, CA, USA) and GE Healthcare (Munich, Germany), have to be interpreted accordingly by the analysis software.Fig. 10


The state of the art in the analysis of two-dimensional gel electrophoresis images.

Berth M, Moser FM, Kolbe M, Bernhardt J - Appl. Microbiol. Biotechnol. (2007)

Example of a gray level calibration curve that is used in special image file formats. Gray levels found in the image file have to be interpreted according to the curve before being summed up for quantitation. The curve has lower slope in the low intensity range resulting in better quantitative resolution for weak signals
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2279157&req=5

Fig10: Example of a gray level calibration curve that is used in special image file formats. Gray levels found in the image file have to be interpreted according to the curve before being summed up for quantitation. The curve has lower slope in the low intensity range resulting in better quantitative resolution for weak signals
Mentions: Calibration inherent in the file format (Fig. 10). Some imaging devices can measure more intensity values than what fit into the available image file formats. For example, if the imaging device can measure a range of 120,000 intensity values, this range cannot be stored into a 16-bit TIFF image because the file format only provides 65,536 possible gray levels per pixel. One way to deal with this is to transform the measured intensity values linearly into the range of gray levels in the image file. Alternatively, because, for lower signal intensities, higher accuracy is desirable, a nonlinear function (e.g., square root transform as illustrated in Fig. 10) is applied by some imaging devices. This provides a more precise representation of lower-intensity pixels at the price of lower accuracy for high intensities. The corresponding vendor-specific file formats, e.g., Fuji’s IMG/INF format (Fujifilm, Düsseldorf, Germany) and the GEL format used in devices by Molecular Dynamics (Sunnyvale, CA, USA) and GE Healthcare (Munich, Germany), have to be interpreted accordingly by the analysis software.Fig. 10

Bottom Line: Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments.Challenges for analysis software as well as good practices are highlighted.We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

View Article: PubMed Central - PubMed

Affiliation: DECODON GmbH, Rathenau-Strasse 49a, 17489 Greifswald, Germany.

ABSTRACT
Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

Show MeSH
Related in: MedlinePlus