ArrayQuest: A web resource for the analysis of DNA microarray data

Array Genetics, Inc,, 59 Great Quarter Road, Newtown, CT 06482, USA.
BMC Bioinformatics (Impact Factor: 2.58). 02/2005; 6(1):287. DOI: 10.1186/1471-2105-6-287
Source: PubMed


Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools.
Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1) it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2) new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3) input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC) DNA Microarray Database or Gene Expression Omnibus (GEO)) or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4) analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data.
ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at

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    • "DNA microarray hybridization data (processed by MAS4 algorithm) for Nkx2.5 wild-type, heterozygous and homozygous cardiothoracic regions from E9.5 embryos was obtained directly from the CardioGenomics website * . DNA microarray hybridization data for P19CL6 cells was normalized using the ArrayQuest webtool (Argraves et al., 2005) to implement the Bioconductor (Gentleman et al., 2004) build of GCRMA(Wu et al., 2004). Affymetrix detection (presence and absence) scores and normalized hybridization values for E10.5 SHF and E12.5 heart samples were obtained using the Bioconductor MAS5 algorithm. "
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    ABSTRACT: Nkx2.5, a transcription factor implicated in human congenital heart disease, is required for regulation of second heart field (SHF) progenitors contributing to outflow tract (OFT). Here, we define a set of genes (Lrrn1, Elovl2, Safb, Slc39a6, Khdrbs1, Hoxb4, Fez1, Ccdc117, Jarid2, Nrcam, and Enpp3) expressed in SHF containing pharyngeal arch tissue whose regulation is dependent on Nkx2.5. Further investigation shows that Jarid2, which has been implicated in OFT morphogenesis, is a direct target of Nkx2.5 regulation. Jarid2 expression was up-regulated in SHF mesoderm of Nkx2.5-deficient embryos. Chromatin immunoprecipitation analysis showed Nkx2.5 interaction with consensus binding sites in the Jarid2 promoter in pharyngeal arch cells. Finally, Jarid2 promoter activity and mRNA expression levels were down-regulated by Nkx2.5 overexpression. Given the role of Jarid2 as a regulator of early cardiac proliferation, these findings highlight Jarid2 as one of several potential mediators of the critical role played by Nkx2.5 during OFT morphogenesis.
    Developmental Dynamics 07/2010; 239(7):2024-33. DOI:10.1002/dvdy.22341 · 2.38 Impact Factor
    • "from the Medical University of South Carolina. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with differentially expressed genes were also identified and hierarchical clustering and heat mapping of all the genes and of the genes in each KEGG pathway were performed [21]. "
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    Autoimmunity 10/2009; 43(2):131-9. DOI:10.3109/08916930903225229 · 2.71 Impact Factor
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    • "Contingency tables, however, are not available in other tools except Pomelo II. Several other tools make it explicit that they run in clusters (20,33), which allows for load balancing and swapping jobs to idle nodes. However, with the exception of EMAAS (18), parallel computing seems not to be used by any other tools. "
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    ABSTRACT: Pomelo II ( is an open-source, web-based, freely available tool for the analysis of gene (and protein) expression and tissue array data. Pomelo II implements: permutation-based tests for class comparisons (t-test, ANOVA) and regression; survival analysis using Cox model; contingency table analysis with Fisher's exact test; linear models (of which t-test and ANOVA are especial cases) that allow additional covariates for complex experimental designs and use empirical Bayes moderated statistics. Permutation-based and Cox model analysis use parallel computing, which permits taking advantage of multicore CPUs and computing clusters. Access to, and further analysis of, additional biological information and annotations (PubMed references, Gene Ontology terms, KEGG and Reactome pathways) are available either for individual genes (from clickable links in tables and figures) or sets of genes. The source code is available, allowing for extending and reusing the software. A comprehensive test suite is also available, and covers both the user interface and the numerical results. The possibility of including additional covariates, parallelization of computation, open-source availability of the code and comprehensive testing suite make Pomelo II a unique tool.
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