Analyzing Two-Dimensional Gel Images

Seillier-Moiseiwitsch, Françoise; Lee, Kwan R.; Hang, Y; Marten, Mark R.; Raman, Babu

doi:10.1080/09332480.2003.10554869

Cited by 9 publications

(5 citation statements)

References 22 publications

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“…The 2-DE gel method involves separation of proteins in two dimensions: in one dimension, proteins are separated due to their differences in charge by isoelectric focusing and in the other dimension proteins are separated due to their differences in molecular weight by sodium dodecyl sulfate polyacrylamide gel electrophoresis. There are several issues involved in analyzing 2-DE gel image data [2,3]. Statistical techniques can effectively locate differentially expressed proteins, and thus are extremely useful for reducing costs by decreasing the number of spots that are to be further analyzed using more accurate albeit more expensive techniques such as mass spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

Independent component analysis of 2‐D electrophoresis gels

et al. 2008

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We present a novel application of independent component analysis (ICA), an exploratory data analysis technique, to two-dimensional electrophoresis (2-DE) gels, which have been used to analyze differentially expressed proteins across groups. Unlike currently used pixel-wise statistical tests, ICA is a data-driven approach that utilizes the information contained in the entire gel data. We also apply ICA on wavelet-transformed 2-DE gels to address the high dimensionality and noise problems typically found in 2-DE gels. Also, we use an analysis-of-variance (ANOVA) approach as a benchmark for comparison. Using simulated data, we show that ICA detects the group differences accurately in both the spatial and wavelet domains. We also apply these techniques to real 2-DE gels. ICA proves to be much faster than ANOVA, and unlike ANOVA it does not depend on the selection of a threshold. Application of principal component analysis reduces the dimensionality and tends to improve the performance by reducing the noise.

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Section: Introductionmentioning

confidence: 99%

Independent component analysis of 2‐D electrophoresis gels

et al. 2008

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“…Statistical problems involved in gel analysis have been discussed [34,[36][37][38][39]. In this paper we consider two approaches, the spot by spot approach (or univariate analysis) where the test statistic for testing the hypothesis H j is based on the data observed for the spot j only, and the global approach (or multivariate analysis) where the test of H j is based on the results of an analysis of variance considering all the observations together.…”

Section: Statistical Models and Testing Methodsmentioning

confidence: 99%

Statistics for proteomics: Experimental design and 2-DE differential analysis

Chich¹,

David²,

Villers³

et al. 2007

Journal of Chromatography B

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“…The main steps in the differential analysis of 2D gels are as follows (Roy et al, 2003). First, one applies procedures to filter out various kinds of noise present on the images.…”

Section: Introductionmentioning

confidence: 99%

Region-based statistical analysis of 2D PAGE images

Feng

Seillier-Moiseiwitsch

Korostyshevskiy

2011

Computational Statistics & Data Analysis

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A new comprehensive procedure for statistical analysis of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) images is proposed, including protein region quantification, normalization and statistical analysis. Protein regions are defined by the master watershed map that is obtained from the mean gel. By working with these protein regions, the approach bypasses the current bottleneck in the analysis of 2D PAGE images: it does not require spot matching. Background correction is implemented in each protein region by local segmentation. Two-dimensional locally weighted smoothing (LOESS) is proposed to remove any systematic bias after quantification of protein regions. Proteins are separated into mutually independent sets based on detected correlations, and a multivariate analysis is used on each set to detect the group effect. A strategy for multiple hypothesis testing based on this multivariate approach combined with the usual Benjamini-Hochberg FDR procedure is formulated and applied to the differential analysis of 2D PAGE images. Each step in the analytical protocol is shown by using an actual dataset. The effectiveness of the proposed methodology is shown using simulated gels in comparison with the commercial software packages PDQuest and Dymension. We also introduce a new procedure for simulating gel images.

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Analyzing Two-Dimensional Gel Images

Cited by 9 publications

References 22 publications

Independent component analysis of 2‐D electrophoresis gels

Independent component analysis of 2‐D electrophoresis gels

Statistics for proteomics: Experimental design and 2-DE differential analysis

Region-based statistical analysis of 2D PAGE images

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