ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.
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.
Chung
Hee-Joon
HJ
Seoul National University Biomedical Informatics, Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.
Kim
Mingoo
M
Park
Chan Hee
CH
Kim
Jihoon
J
Kim
Ju Han
JH
D016000:Cluster Analysis; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis; D015398:Signal Transduction; D012984:Software; D018511:Systems Integration; D014584:User-Computer Interface