Independent Component Analysis of Simulated 2D Electrophoresis Gels

Author

Correa, N. ; Safavi, H. ; Wei Xiong ; Roy, Anindya ; Adali, Tulay ; Seillier-Moiseiwitsch, Francoise

Author_Institution

Dept. of CSEE, Maryland Univ., Baltimore, MD

fYear

2006

fDate

6-8 Sept. 2006

Firstpage

397

Lastpage

402

Abstract

We present a novel method to detect differentially expressed proteins in simulated two-dimensional electrophoresis (2DE) gels using spatial independent component analysis (ICA). We use an analysis-of-variance (ANOVA) approach as a benchmark for comparison and show that it yields improved detection power compared to currently used t-test based methods for 2DE gel analysis. However, ICA proves to be much faster than ANOVA and unlike ANOVA, it does not depend on any threshold. We also use ICA on wavelet-transformed 2DE gels. ICA in the wavelet domain offers increase in speed, and also, better performance for misaligned gels as compared to the ICA in the spatial domain.

Keywords

biochemistry; bioelectric phenomena; biological techniques; electrophoresis; independent component analysis; molecular biophysics; proteins; wavelet transforms; ANOVA approach; analysis-of-variance approach; differentially expressed protein detection; independent component analysis; simulated 2D electrophoresis gels; spatial ICA; wavelet-transformed 2DE gels; Analysis of variance; Analytical models; Electrokinetics; Independent component analysis; Medical simulation; Performance analysis; Principal component analysis; Proteins; Testing; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on

Conference_Location

Arlington, VA

ISSN

1551-2541

Print_ISBN

1-4244-0656-0

Electronic_ISBN

1551-2541

Type

conf

DOI

10.1109/MLSP.2006.275582

Filename

4053681