GenMAPP 2: new features and resources for pathway analysis

被引:189
|
作者
Salomonis, Nathan
Hanspers, Kristina
Zambon, Alexander C.
Vranizan, Karen
Lawlor, Steven C.
Dahlquist, Kam D.
Doniger, Scott W.
Stuart, Josh
Conklin, Bruce R.
Pico, Alexander R.
机构
[1] Gladstone Inst Cardiovasc Dis, San Francisco, CA 94158 USA
[2] Univ Calif San Francisco, Pharmaceut Sci & Pharmacogenom Grad Program, San Francisco, CA 94143 USA
[3] Univ Calif Berkeley, Funct Genom Lab, Berkeley, CA 94720 USA
[4] Loyola Marymount Univ, Dept Biol, Los Angeles, CA 90045 USA
[5] Washington Univ, Sch Med, Computat Biol Grad Program, St Louis, MO 63108 USA
[6] Univ Calif Santa Cruz, Dept Biomol Engn, Santa Cruz, CA 95064 USA
[7] Univ Calif San Francisco, Dept Med, San Francisco, CA 94143 USA
[8] Univ Calif San Francisco, Dept Mol & Cellular Pharmacol, San Francisco, CA 94143 USA
关键词
D O I
10.1186/1471-2105-8-217
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses. Results: To address the growing needs of the microarray community we have released version 2 of Gene Map Annotator and Pathway Profiler (GenMAPP), a new GenMAPP database schema, and integrated resources for pathway analysis. We have redesigned the GenMAPP database to support multiple gene annotations and species as well as custom species database creation for a potentially unlimited number of species. We have expanded our pathway resources by utilizing homology information to translate pathway content between species and extending existing pathways with data derived from conserved protein interactions and coexpression. We have implemented a new mode of data visualization to support analysis of complex data, including time-course, single nucleotide polymorphism (SNP), and splicing. GenMAPP version 2 also offers innovative ways to display and share data by incorporating HTML export of analyses for entire sets of pathways as organized web pages. Conclusion: GenMAPP version 2 provides a means to rapidly interrogate complex experimental data for pathway-level changes in a diverse range of organisms.
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页数:12
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