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Beyond Bioinformatics | |
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Title |
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SDED: A novel filter method for cancer-related gene selection
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Authors |
Wenlong Xu1, Minghui Wang2, Xianghua Zhang1, Lirong Wang1, Huanqing Feng1, *
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Affiliation |
1Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China; 2The College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100022, China
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86 551 3601800; * Corresponding author
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Article Type |
Hypothesis
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Date |
received December 19, 2007; revised March 13, 2008; accepted April 04, 2008; published April 11, 2008
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Abstract |
Gene selection is to detect the most significantly expressed genes under different conditions expression data. The current challenge in gene selection is the comparison of a large number of genes with limited patient samples. Thus it is trivial task in simple statistical analysis. Various statistical measurements are adopted by filter methods applied in gene selection studies. Their ability to discriminate phenotypes is crucial in classification and selection. Here we describe the standard deviation error distribution (SDED) method for gene selection. It utilizes variations within-class and among-class in gene expression data. We tested the method using 4 leukemia datasets available in the public domain. The method was compared with the GS2 and CHO methods. The Prediction accuracies by SDED are better than both GS2 and CHO for different datasets. These are 0.8-4.2% and 1.6-8.4% more that in GS2 and CHO. The related OMIM annotations and KEGG pathways analyses verified that SDED can pick out more 4.0% and 6.1% genes with biological significance than GS2 and CHO, respectively.
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Keywords |
gene selection; filter method; support vector machine; SDED
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Citation |
Xu et al., Bioinformation 2(7): 301-303 (2008)
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Edited by |
P. Kangueane
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ISSN |
0973-2063
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Publisher |
Biomedical Informatics Publishing Group
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Copyright |
Publisher
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Copyright Transfer Agreement |
The authors of published articles in Bioinformation automatically transfer the copyright to the publisher upon formal acceptance. However, the authors reserve right to use the information contained in the article for non commercial purposes.
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License |
This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
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