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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.

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Screen shots of MiMiR Online. a: Screen shot of MiMiR Online showing the data sharing functionality. b: Screen shot of MiMiR Online showing the left hand tree view icons for navigation and the right hand panel showing the Experiment Details of a public experiment in MiMiR. Several experiments can be opened simultaneously and users can toggle between them using the top panel of tabs. Information including the study description, number of biosources (organisms), biosamples and hybridisations performed, chip type(s) used, private/public status, ArrayExpress accession number and date of public release (if relevant), as well as the active PubMed link if the experiment has been published, can be accessed. MGED Ontology terms are used systematically e.g. Category MO:PerturbationalDesign, Value MO:compound_treatment_design) and experimental factors (e.g. Category MO:compound, Value H2O2_-0.04). The tree view also gives access to information on the Biomaterials i.e. Biosources (whole organisms), Biosamples (material derived from the biosources) and the consecutive treatment steps generating the labelled extract to be hybridised on arrays. Different icons are used in the tree to visually facilitate navigation between the different procedure stages.
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Figure 3: Screen shots of MiMiR Online. a: Screen shot of MiMiR Online showing the data sharing functionality. b: Screen shot of MiMiR Online showing the left hand tree view icons for navigation and the right hand panel showing the Experiment Details of a public experiment in MiMiR. Several experiments can be opened simultaneously and users can toggle between them using the top panel of tabs. Information including the study description, number of biosources (organisms), biosamples and hybridisations performed, chip type(s) used, private/public status, ArrayExpress accession number and date of public release (if relevant), as well as the active PubMed link if the experiment has been published, can be accessed. MGED Ontology terms are used systematically e.g. Category MO:PerturbationalDesign, Value MO:compound_treatment_design) and experimental factors (e.g. Category MO:compound, Value H2O2_-0.04). The tree view also gives access to information on the Biomaterials i.e. Biosources (whole organisms), Biosamples (material derived from the biosources) and the consecutive treatment steps generating the labelled extract to be hybridised on arrays. Different icons are used in the tree to visually facilitate navigation between the different procedure stages.

Mentions: Detailed sample/treatment information for each experiment can be accessed via MiMiR Online web front end that communicates with the MiMiR database via the middleware layer. Registered users can view and access public datasets in MiMiR and users with appropriate rights for an experiment (e.g. the owner of a data set) can share un-published experiments with other registered users of the system via the interface (Figure 3a). Two international consortia are currently using MiMiR to centralise and share un-published datasets (European Rat tools for functional Genomics (EURATools) and Wellcome Trust Cardiovascular Functional Genomics consortium).


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 MiMiR Online. a: Screen shot of MiMiR Online showing the data sharing functionality. b: Screen shot of MiMiR Online showing the left hand tree view icons for navigation and the right hand panel showing the Experiment Details of a public experiment in MiMiR. Several experiments can be opened simultaneously and users can toggle between them using the top panel of tabs. Information including the study description, number of biosources (organisms), biosamples and hybridisations performed, chip type(s) used, private/public status, ArrayExpress accession number and date of public release (if relevant), as well as the active PubMed link if the experiment has been published, can be accessed. MGED Ontology terms are used systematically e.g. Category MO:PerturbationalDesign, Value MO:compound_treatment_design) and experimental factors (e.g. Category MO:compound, Value H2O2_-0.04). The tree view also gives access to information on the Biomaterials i.e. Biosources (whole organisms), Biosamples (material derived from the biosources) and the consecutive treatment steps generating the labelled extract to be hybridised on arrays. Different icons are used in the tree to visually facilitate navigation between the different procedure stages.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: Screen shots of MiMiR Online. a: Screen shot of MiMiR Online showing the data sharing functionality. b: Screen shot of MiMiR Online showing the left hand tree view icons for navigation and the right hand panel showing the Experiment Details of a public experiment in MiMiR. Several experiments can be opened simultaneously and users can toggle between them using the top panel of tabs. Information including the study description, number of biosources (organisms), biosamples and hybridisations performed, chip type(s) used, private/public status, ArrayExpress accession number and date of public release (if relevant), as well as the active PubMed link if the experiment has been published, can be accessed. MGED Ontology terms are used systematically e.g. Category MO:PerturbationalDesign, Value MO:compound_treatment_design) and experimental factors (e.g. Category MO:compound, Value H2O2_-0.04). The tree view also gives access to information on the Biomaterials i.e. Biosources (whole organisms), Biosamples (material derived from the biosources) and the consecutive treatment steps generating the labelled extract to be hybridised on arrays. Different icons are used in the tree to visually facilitate navigation between the different procedure stages.
Mentions: Detailed sample/treatment information for each experiment can be accessed via MiMiR Online web front end that communicates with the MiMiR database via the middleware layer. Registered users can view and access public datasets in MiMiR and users with appropriate rights for an experiment (e.g. the owner of a data set) can share un-published experiments with other registered users of the system via the interface (Figure 3a). Two international consortia are currently using MiMiR to centralise and share un-published datasets (European Rat tools for functional Genomics (EURATools) and Wellcome Trust Cardiovascular Functional Genomics consortium).

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