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PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In...

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Autores principales: Pan, Deyun, Sun, Ning, Cheung, Kei-Hoi, Guan, Zhong, Ma, Ligeng, Holford, Matthew, Deng, Xingwang, Zhao, Hongyu
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2003
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC302111/
https://www.ncbi.nlm.nih.gov/pubmed/14604444
http://dx.doi.org/10.1186/1471-2105-4-56
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author Pan, Deyun
Sun, Ning
Cheung, Kei-Hoi
Guan, Zhong
Ma, Ligeng
Holford, Matthew
Deng, Xingwang
Zhao, Hongyu
author_facet Pan, Deyun
Sun, Ning
Cheung, Kei-Hoi
Guan, Zhong
Ma, Ligeng
Holford, Matthew
Deng, Xingwang
Zhao, Hongyu
author_sort Pan, Deyun
collection PubMed
description BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).
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spelling pubmed-3021112003-12-30 PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis Pan, Deyun Sun, Ning Cheung, Kei-Hoi Guan, Zhong Ma, Ligeng Holford, Matthew Deng, Xingwang Zhao, Hongyu BMC Bioinformatics Software BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). BioMed Central 2003-11-07 /pmc/articles/PMC302111/ /pubmed/14604444 http://dx.doi.org/10.1186/1471-2105-4-56 Text en Copyright © 2003 Pan et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
spellingShingle Software
Pan, Deyun
Sun, Ning
Cheung, Kei-Hoi
Guan, Zhong
Ma, Ligeng
Holford, Matthew
Deng, Xingwang
Zhao, Hongyu
PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis
title PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis
title_full PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis
title_fullStr PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis
title_full_unstemmed PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis
title_short PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis
title_sort pathmapa: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for arabidopsis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC302111/
https://www.ncbi.nlm.nih.gov/pubmed/14604444
http://dx.doi.org/10.1186/1471-2105-4-56
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