ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.

Hee-Joon Chung; Mingoo Kim; Chan Hee Park; Jihoon Kim; Ju Han Kim

doi:10.1093/nar/gkh476

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ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.

Hee-Joon Chung·Mingoo Kim·Chan Hee Park·Jihoon Kim·Ju Han Kim

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Abstract

Biological pathways can provide key information on the organization of biological systems. ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data for integrated biological pathway resources using Scalable Vector Graphics (SVG). By integrating major bio-databases and searching pathway resources, ArrayXPath automatically maps different types of identifiers from microarray probes and pathway elements. When one inputs gene-expression clusters, ArrayXPath produces a list of the best matching pathways for each cluster. We applied Fisher's exact test and the false discovery rate (FDR) to evaluate the statistical significance of the association between a cluster and a pathway while correcting the multiple-comparison problem. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of pathways integrated with gene-expression profiles.

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Cluster Analysis Computer Graphics Data Interpretation, Statistical Gene Expression Profiling Internet Oligonucleotide Array Sequence Analysis Signal Transduction Software Systems Integration User-Computer Interface Journal Article

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BibTeX RIS

Hee-Joon Chung, Mingoo Kim, Chan Hee Park, Jihoon Kim, Ju Han Kim. 2004-07-01. ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.. https://doi.org/10.1093/nar%2Fgkh476

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