EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

Barton, Geraint; Abbott, James; Chiba, Norie; Huang, Daniel; Huang, Yanyan; Krznaric, Marko; Mack-Smith, J.; Saleem, Ammar; Sherman, Brad T.; Tiwari, Brijesh K.; Tomlinson, Christopher; Aitman, Timothy J.; Darlington, John; Gamé, Laurence; Sternberg, Michael J.E.; Butcher, Sarah

doi:10.1186/1471-2105-9-493

Cited by 13 publications

(15 citation statements)

References 20 publications

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“…In databases like Oncomine, Flymine [13], Ingenuity, EMAAS [14], MiMiR [15] and many others around the world, microarray data can be imported, queried and visualized for a selected gene across all analyses or for multiple genes in a selected analysis. However, none of these databases provide an analysis platform for absolute gene expression profiling.…”

Section: Discussionmentioning

confidence: 99%

Gene Expression Commons: An Open Platform for Absolute Gene Expression Profiling

et al. 2012

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Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named “Gene Expression Commons” (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

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Section: Discussionmentioning

confidence: 99%

Gene Expression Commons: An Open Platform for Absolute Gene Expression Profiling

et al. 2012

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“…Visualisation of consensus regions together with gene representation allows the explorative assessment of the data. Another project is the Extensible MicroArray Analysis System (EMAAS) application created by Butcher and colleagues from Imperial College (UK) and the National Cancer Institute at Frederick (MD, USA) to provide simple, robust access to updated resources for microarray analysis [19]. When looking at specific gene information, their program generates an interactive expression profile plot and concomitantly brings forth the respective GeneCards information, thereby allowing further scrutiny of experimental data.…”

Section: Genecards Utilisation Examplesmentioning

confidence: 99%

In-silico human genomics with GeneCards

et al. 2011

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Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org). This human gene compendium was created to help to introduce order into the increasing chaos of information flow. As a consequence of viewing details and deep links related to specific genes, users have often requested enhanced capabilities, such that, over time, GeneCards has blossomed into a suite of tools (including GeneDecks, GeneALaCart, GeneLoc, GeneNote and GeneAnnot) for a variety of analyses of both single human genes and sets thereof. In this paper, we focus on inhouse and external research activities which have been enabled, enhanced, complemented and, in some cases, motivated by GeneCards. In turn, such interactions have often inspired and propelled improvements in GeneCards. We describe here the evolution and architecture of this project, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.

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“…The MiMiR middleware is used by EMAAS to securely access the appropriate experimental information, using Java Server Pages (JSPs) and Servlets. EMAAS is currently being used to perform data quality assessment, pre-processing, statistical analysis and functional enrichment analysis of Affymetrix 3' and Exon/Gene ST arrays, with scope to add further functionality for other platforms such as Illumina, Agilent and Codelink arrays [ 20 ].…”

Section: Construction and Contentmentioning

confidence: 99%

“…Here we describe new software components and enhancements of the original infrastructure that allow researchers to securely submit, access, share and analyse microarray and meta-data. Specifically, we have created: (i) a re-engineered hardware and software architecture that protects the MiMiR database integrity and enables secure online sharing of unpublished and public data amongst registered users; (ii) a new web based annotation tool allowing researchers to easily and quickly submit information about their experiments and samples; (iii) new sophisticated curation and annotation tools which automatically create annotated experiments in MiMiR and enable in-house annotators to check it and add ontology terms and systematic naming conventions; (iv) a clinical Data Mapping Tool to securely capture clinical information in a systematic way within an appropriate ethical framework; (v) a new user-friendly web interface that is used by researchers to visualise extensive experimental annotation, to download data and quality assessment reports and to share un-published datasets with collaborators or other registered users of the system; (vi) a re-engineered MAGE-ML pipeline for exporting experiments from MiMiR into the ArrayExpress repository or into the Rosetta Resolver package for data analysis; (vii) programmatic access to MiMiR from the new open source microarray data analysis software package EMAAS [ 20 ], allowing users to export selected data and associated meta-data for analysis.…”

Section: Introductionmentioning

confidence: 99%

MiMiR – an integrated platform for microarray data sharing, mining and analysis

et al. 2008

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BackgroundDespite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data.ResultsA user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package.ConclusionThe new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

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EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

Cited by 13 publications

References 20 publications

Gene Expression Commons: An Open Platform for Absolute Gene Expression Profiling

Gene Expression Commons: An Open Platform for Absolute Gene Expression Profiling

In-silico human genomics with GeneCards

MiMiR – an integrated platform for microarray data sharing, mining and analysis

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