p-BioSPRE-an information and communication technology framework for transnational biomaterial sharing and access

Biobanks represent key resources for clinico-genomic research and are needed to pave the way to personalised medicine. To achieve this goal, it is crucial that scientists can securely access and share high-quality biomaterial and related data. Therefore, there is a growing interest in integrating biobanks into larger biomedical information and communication technology (ICT) infrastructures. The European project p-medicine is currently building an innovative ICT infrastructure to meet this need. This platform provides tools and services for conducting research and clinical trials in personalised medicine. In this paper, we describe one of its main components, the biobank access framework p-BioSPRE (p-medicine Biospecimen Search and Project Request Engine). This generic framework enables and simplifies access to existing biobanks, but also to offer own biomaterial collections to research communities, and to manage biobank specimens and related clinical data over the ObTiMA Trial Biomaterial Manager. p-BioSPRE takes into consideration all relevant ethical and legal standards, e.g., safeguarding donors’ personal rights and enabling biobanks to keep control over the donated material and related data. The framework thus enables secure sharing of biomaterial within open and closed research communities, while flexibly integrating related clinical and omics data. Although the development of the framework is mainly driven by user scenarios from the cancer domain, in this case, acute lymphoblastic leukaemia and Wilms tumour, it can be extended to further disease entities.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.