Limits...
MiMiR--an integrated platform for microarray data sharing, mining and analysis.

Tomlinson C, Thimma M, Alexandrakis S, Castillo T, Dennis JL, Brooks A, Bradley T, Turnbull C, Blaveri E, Barton G, Chiba N, Maratou K, Soutter P, Aitman T, Game L - BMC Bioinformatics (2008)

Bottom Line: The 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Microarray Centre, MRC Clinical Sciences Centre and Imperial College, Hammersmith Hospital, London, UK. chris.tomlinson@imperial.ac.uk

ABSTRACT

Background: Despite 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.

Results: A 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.

Conclusion: The 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.

Show MeSH
Screen shots of the MiMiR-EMAAS interface, showing a guest user viewing and selecting data and meta-data from a MiMiR experiment to export into EMAAS for analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2572073&req=5

Figure 4: Screen shots of the MiMiR-EMAAS interface, showing a guest user viewing and selecting data and meta-data from a MiMiR experiment to export into EMAAS for analysis.

Mentions: EMAAS (Extensible Micro Array Analysis System) is a new web e-support application developed for microarray data analysis . EMAAS utilizes grid technologies to perform analysis tasks, programmatically calling analysis packages such as R-BioConductor and the Affymetrix Power Tools . EMAAS also uses web services to various online facilities such as DAVID [22], CELSIUS [23] and GeneCards [24]. MiMiR registered users can inspect MiMiR experiments and associated information from the EMAAS-MiMiR integrated interface and can select specific data files and associated meta-data to be imported into EMAAS for analysis (Figure 4). 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].


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

Tomlinson C, Thimma M, Alexandrakis S, Castillo T, Dennis JL, Brooks A, Bradley T, Turnbull C, Blaveri E, Barton G, Chiba N, Maratou K, Soutter P, Aitman T, Game L - BMC Bioinformatics (2008)

Screen shots of the MiMiR-EMAAS interface, showing a guest user viewing and selecting data and meta-data from a MiMiR experiment to export into EMAAS for analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2572073&req=5

Figure 4: Screen shots of the MiMiR-EMAAS interface, showing a guest user viewing and selecting data and meta-data from a MiMiR experiment to export into EMAAS for analysis.
Mentions: EMAAS (Extensible Micro Array Analysis System) is a new web e-support application developed for microarray data analysis . EMAAS utilizes grid technologies to perform analysis tasks, programmatically calling analysis packages such as R-BioConductor and the Affymetrix Power Tools . EMAAS also uses web services to various online facilities such as DAVID [22], CELSIUS [23] and GeneCards [24]. MiMiR registered users can inspect MiMiR experiments and associated information from the EMAAS-MiMiR integrated interface and can select specific data files and associated meta-data to be imported into EMAAS for analysis (Figure 4). 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].

Bottom Line: The 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Microarray Centre, MRC Clinical Sciences Centre and Imperial College, Hammersmith Hospital, London, UK. chris.tomlinson@imperial.ac.uk

ABSTRACT

Background: Despite 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.

Results: A 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.

Conclusion: The 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.

Show MeSH