Dataset Information

CADRE: the Central Aspergillus Data REpository 2012.

ABSTRACT: The Central Aspergillus Data REpository (CADRE; http://www.cadre-genomes.org.uk) is a public resource for genomic data extracted from species of Aspergillus. It provides an array of online tools for searching and visualising features of this significant fungal genus. CADRE arose from a need within the medical community to understand the human pathogen Aspergillus fumigatus. Due to the paucity of Aspergillus genomic resources 10 years ago, the long-term goal of this project was to collate and maintain Aspergillus genomes as they became available. Since our first release in 2004, the resource has expanded to encompass annotated sequence for eight other Aspergilli and provides much needed support to the international Aspergillus research community. Recent developments, however, in sequencing technology are creating a vast amount of genomic data and, as a result, we shortly expect a tidal wave of Aspergillus data. In preparation for this, we have upgraded the database and software suite. This not only enables better management of more complex data sets, but also improves annotation by providing access to genome comparison data and the integration of high-throughput data.

SUBMITTER: Mabey Gilsenan J

PROVIDER: S-EPMC3245145 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Publications

CADRE: the Central Aspergillus Data REpository 2012.

Mabey Gilsenan Jane J Cooley John J Bowyer Paul P

Nucleic acids research 20111112 Database issue

The Central Aspergillus Data REpository (CADRE; http://www.cadre-genomes.org.uk) is a public resource for genomic data extracted from species of Aspergillus. It provides an array of online tools for searching and visualising features of this significant fungal genus. CADRE arose from a need within the medical community to understand the human pathogen Aspergillus fumigatus. Due to the paucity of Aspergillus genomic resources 10 years ago, the long-term goal of this project was to collate and mai ...[more]

PMID: 22080563

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Project description:BackgroundCalls have been made for increased access to individual participant data (IPD) from clinical trials, to ensure that complete evidence is available. However, despite the obvious benefits, progress towards this is frustratingly slow. In the meantime, many systematic reviews have already collected IPD from clinical trials. We propose that a central repository for these IPD should be established to ensure that these datasets are safeguarded and made available for use by others, building on the strengths and advantages of the collaborative groups that have been brought together in developing the datasets.ObjectiveEvaluate the level of support, and identify major issues, for establishing a central repository of IPD.DesignOn-line survey with email reminders.Participants71 reviewers affiliated with the Cochrane Collaboration's IPD Meta-analysis Methods Group were invited to participate.Results30 (42%) invitees responded: 28 (93%) had been involved in an IPD review and 24 (80%) had been involved in a randomised trial. 25 (83%) agreed that a central repository was a good idea and 25 (83%) agreed that they would provide their IPD for central storage. Several benefits of a central repository were noted: safeguarding and standardisation of data, increased efficiency of IPD meta-analyses, knowledge advancement, and facilitating future clinical, and methodological research. The main concerns were gaining permission from trial data owners, uncertainty about the purpose of the repository, potential resource implications, and increased workload for IPD reviewers. Restricted access requiring approval, data security, anonymisation of data, and oversight committees were highlighted as issues under governance of the repository.ConclusionThere is support in this community of IPD reviewers, many of whom are also involved in clinical trials, for storing IPD in a central repository. Results from this survey are informing further work on developing a repository of IPD which is currently underway by our group.

Project description:BackgroundTissue microarray (TMA) technology has been developed to facilitate large, genome-scale molecular pathology studies. This technique provides a high-throughput method for analyzing a large cohort of clinical specimens in a single experiment thereby permitting the parallel analysis of molecular alterations (at the DNA, RNA, or protein level) in thousands of tissue specimens. As a vast quantity of data can be generated in a single TMA experiment a systematic approach is required for the storage and analysis of such data.DescriptionTo analyse TMA output a relational database (known as TmaDB) has been developed to collate all aspects of information relating to TMAs. These data include the TMA construction protocol, experimental protocol and results from the various immunocytological and histochemical staining experiments including the scanned images for each of the TMA cores. Furthermore the database contains pathological information associated with each of the specimens on the TMA slide, the location of the various TMAs and the individual specimen blocks (from which cores were taken) in the laboratory and their current status i.e. if they can be sectioned into further slides or if they are exhausted. TmaDB has been designed to incorporate and extend many of the published common data elements and the XML format for TMA experiments and is therefore compatible with the TMA data exchange specifications developed by the Association for Pathology Informatics community. Finally the design of the database is made flexible such that TMA experiments from several types of cancer can be stored in a single database, which incorporates the national minimum data set required for pathology reports supported by the Royal College of Pathologists (UK).ConclusionTmaDB will provide a comprehensive repository for TMA data such that a large number of results from the numerous immunostaining experiments can be efficiently compared for each of the TMA cores. This will allow a systematic, large-scale comparison of tumour samples to facilitate the identification of gene products of clinical importance such as therapeutic or prognostic markers. In addition this work will contribute to the establishment of a standard for reporting TMA data analogous to MIAME in the description of microarray data.

Dataset Information

CADRE: the Central Aspergillus Data REpository 2012.

Publications

CADRE: the Central Aspergillus Data REpository 2012.

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