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Gene-set activity toolbox (GAT): A platform for microarray-based cancer diagnosis using an integrative gene-set analysis approach
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Document Title
Gene-set activity toolbox (GAT): A platform for microarray-based cancer diagnosis using an integrative gene-set analysis approach
Author
Engchuan W, Meechai A, Tongsima S, Doungpan N, Chan JH
Name from Authors Collection
Affiliations
King Mongkuts University of Technology Thonburi; King Mongkuts University of Technology Thonburi; National Science & Technology Development Agency - Thailand; National Center Genetic Engineering & Biotechnology (BIOTEC); King Mongkuts University of Technology Thonburi
Type
Article
Source Title
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
ISSN
0219-7200
Year
2016
Volume
14
Issue
5
Open Access
hybrid
Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI
10.1142/S0219720016500153
Format
Abstract
Cancer is a complex disease that cannot be diagnosed reliably using only single gene expression analysis. Using gene-set analysis on high throughput gene expression profiling controlled by various environmental factors is a commonly adopted technique used by the cancer research community. This work develops a comprehensive gene expression analysis tool (gene-set activity toolbox: (GAT)) that is implemented with data retriever, traditional data pre-processing, several gene-set analysis methods, network visualization and data mining tools. The gene-set analysis methods are used to identify subsets of phenotype-relevant genes that will be used to build a classification model. To evaluate GAT performance, we performed a cross-dataset validation study on three common cancers namely colorectal, breast and lung cancers. The results show that GAT can be used to build a reasonable disease diagnostic model and the predicted markers have biological relevance. GAT can be accessed from http://gat.sit.kmutt.ac.th where GAT's java library for gene-set analysis, simple classification and a database with three cancer benchmark datasets can be downloaded.
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Knowledge Taxonomy Level 3
Funding Sponsor
National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand; Office of Higher Education Grant (Wor-1); Thailand Research Fund [RSA58-80061]
License
CC BY
Rights
Authors
Publication Source
WOS