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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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Related in: MedlinePlus

Background subtraction using the rolling ball approach
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Fig11: Background subtraction using the rolling ball approach

Mentions: Image background is generated by material that is stained but not part of a protein spot. The method of background subtraction can have a significant influence on spot quantities; therefore, it is important that background quantities are made explicit by the software instead of being silently subtracted from a spot’s quantity. Background levels can vary considerably between regions on a gel and between gels. Some background subtraction methods are based on the gray levels at the spot boundaries, other approaches are based on the entire available image data. One example for a background estimation that is based on the spot boundary is DeCyder’s (GE Healthcare) rule: Background is determined by the tenth percentile value of all intensity values on the boundary. A background model based on local minima was used by Tyson et al. (1986). The Melanie II software (Appel et al. 1997) calculated background based on a polynomial that is fitted to image intensities. A related approach is the rolling ball method (Skolnick 1986) that determines background levels by fitting a sphere into the 3-D “landscape” of the image (see Fig. 11). The sphere needs to be large enough such that the ball will not go too deep into the spots. Background levels are then determined relative to the center of the ball when it touches the image surface.Fig. 11


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)

Background subtraction using the rolling ball approach
© Copyright Policy
Related In: Results  -  Collection

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

Fig11: Background subtraction using the rolling ball approach
Mentions: Image background is generated by material that is stained but not part of a protein spot. The method of background subtraction can have a significant influence on spot quantities; therefore, it is important that background quantities are made explicit by the software instead of being silently subtracted from a spot’s quantity. Background levels can vary considerably between regions on a gel and between gels. Some background subtraction methods are based on the gray levels at the spot boundaries, other approaches are based on the entire available image data. One example for a background estimation that is based on the spot boundary is DeCyder’s (GE Healthcare) rule: Background is determined by the tenth percentile value of all intensity values on the boundary. A background model based on local minima was used by Tyson et al. (1986). The Melanie II software (Appel et al. 1997) calculated background based on a polynomial that is fitted to image intensities. A related approach is the rolling ball method (Skolnick 1986) that determines background levels by fitting a sphere into the 3-D “landscape” of the image (see Fig. 11). The sphere needs to be large enough such that the ball will not go too deep into the spots. Background levels are then determined relative to the center of the ball when it touches the image surface.Fig. 11

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