Gudmundur A. Thorisson

The SNP Consortium website: past, present and future

The SNP Consortium website (http://snp.cshl.org) has undergone many changes since its initial conception three years ago. The database back end has been changed from the venerable ACeDB to the more scalable MySQL engine. Users can access the data via gene or single nucleotide polymorphism (SNP) keyword searches and browse or dump SNP data to textfiles. A graphical genome browsing interface shows SNPs mapped onto the genome assembly in the context of externally available gene predictions and other features. SNP allele frequency and genotype data are available via FTP-download and on individual SNP report web pages. SNP linkage maps are available for download and for browsing in a comparative map viewer. All software components of the data coordinating center (DCC) website (http://snp.cshl.org) are open source.

WormBase: a cross-species database for comparative genomics

WormBase (http://www.wormbase.org/) is a web-accessible central data repository for information about Caenorhabditis elegans and related nematodes. The past two years have seen a significant expansion in the biological scope of WormBase, including the integration of large-scale, genome-wide data sets, the inclusion of genome sequence and gene predictions from related species and active literature curation. This expansion of data has also driven the development and refinement of user interfaces and operability, including a new Genome Browser, new searches and facilities for data access and the inclusion of extensive documentation. These advances have expanded WormBase beyond the obvious target audience of C. elegans researchers, to include researchers wishing to explore problems in functional and comparative genomics within the context of a powerful genetic system.

Genotype-phenotype databases: challenges and solutions for the post-genomic era.

The flow of research data concerning the genetic basis of health and disease is rapidly increasing in speed and complexity. In response, many projects are seeking to ensure that there are appropriate informatics tools, systems and databases available to manage and exploit this flood of information. Previous solutions, such as central databases, journal-based publication and manually intensive data curation, are now being enhanced with new systems for federated databases, database publication, and more automated management of data flows and quality control. Along with emerging technologies that enhance connectivity and data retrieval, these advances should help to create a powerful knowledge environment for genotype–phenotype information.

The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button

BackgroundThere is a huge demand on bioinformaticians to provide their biologists with user friendly and scalable software infrastructures to capture, exchange, and exploit the unprecedented amounts of new *omics data. We here present MOLGENIS, a generic, open source, software toolkit to quickly produce the bespoke MOLecular GENetics Information Systems needed.MethodsThe MOLGENIS toolkit provides bioinformaticians with a simple language to model biological data structures and user interfaces. At the push of a button, MOLGENIS’ generator suite automatically translates these models into a feature-rich, ready-to-use web application including database, user interfaces, exchange formats, and scriptable interfaces. Each generator is a template of SQL, JAVA, R, or HTML code that would require much effort to write by hand. This ‘model-driven’ method ensures reuse of best practices and improves quality because the modeling language and generators are shared between all MOLGENIS applications, so that errors are found quickly and improvements are shared easily by a re-generation. A plug-in mechanism ensures that both the generator suite and generated product can be customized just as much as hand-written software.ResultsIn recent years we have successfully evaluated the MOLGENIS toolkit for the rapid prototyping of many types of biomedical applications, including next-generation sequencing, GWAS, QTL, proteomics and biobanking. Writing 500 lines of model XML typically replaces 15,000 lines of hand-written programming code, which allows for quick adaptation if the information system is not yet to the biologist’s satisfaction. Each application generated with MOLGENIS comes with an optimized database back-end, user interfaces for biologists to manage and exploit their data, programming interfaces for bioinformaticians to script analysis tools in R, Java, SOAP, REST/JSON and RDF, a tab-delimited file format to ease upload and exchange of data, and detailed technical documentation. Existing databases can be quickly enhanced with MOLGENIS generated interfaces using the ‘ExtractModel’ procedure.ConclusionsThe MOLGENIS toolkit provides bioinformaticians with a simple model to quickly generate flexible web platforms for all possible genomic, molecular and phenotypic experiments with a richness of interfaces not provided by other tools. All the software and manuals are available free as LGPLv3 open source at http://www.molgenis.org.

HGVbaseG2P: a central genetic association database

The Human Genome Variation database of Genotype to Phenotype information (HGVbaseG2P) is a new central database for summary-level findings produced by human genetic association studies, both large and small. Such a database is needed so that researchers have an easy way to access all the available association study data relevant to their genes, genome regions or diseases of interest. Such a depository will allow true positive signals to be more readily distinguished from false positives (type I error) that fail to consistently replicate. In this paper we describe how HGVbaseG2P has been constructed, and how its data are gathered and organized. We present a range of user-friendly but powerful website tools for searching, browsing and visualizing G2P study findings. HGVbaseG2P is available at http://www.hgvbaseg2p.org.

The role of a bioresource research impact factor as an incentive to share human bioresources

The role of a bioresource research impact factor as an incentive to share human bioresources

Quantifying the use of bioresources for promoting their sharing in scientific research

An increasing portion of biomedical research relies on the use of biobanks and databases. Sharing of such resources is essential for optimizing knowledge production. A major obstacle for sharing bioresources is the lack of recognition for the efforts involved in establishing, maintaining and sharing them, due to, in particular, the absence of adequate tools. Increasing demands on biobanks and databases to improve access should be complemented with efforts of end-users to recognize and acknowledge these resources. An appropriate set of tools must be developed and implemented to measure this impact.To address this issue we propose to measure the use in research of such bioresources as a value of their impact, leading to create an indicator: Bioresource Research Impact Factor (BRIF). Key elements to be assessed are: defining obstacles to sharing samples and data, choosing adequate identifier for bioresources, identifying and weighing parameters to be considered in the metrics, analyzing the role of journal guidelines and policies for resource citing and referencing, assessing policies for resource access and sharing and their influence on bioresource use. This work allows us to propose a framework and foundations for the operational development of BRIF that still requires input from stakeholders within the biomedical community.

An informatics project and online "Knowledge Centre" supporting modern genotype-to-phenotype research.

Explosive growth in the generation of genotype‐to‐phenotype (G2P) data necessitates a concerted effort to tackle the logistical and informatics challenges this presents. The GEN2PHEN Project represents one such effort, with a broad strategy of uniting disparate G2P resources into a hybrid centralized‐federated network. This is achieved through a holistic strategy focussed on three overlapping areas: data input standards and pipelines through which to submit and collect data (data in); federated, independent, extendable, yet interoperable database platforms on which to store and curate widely diverse datasets (data storage); and data formats and mechanisms with which to exchange, combine, and extract data (data exchange and output). To fully leverage this data network, we have constructed the “G2P Knowledge Centre” (http://www.gen2phen.org). This central platform provides holistic searching of the G2P data domain allied with facilities for data annotation and user feedback, access to extensive G2P and informatics resources, and tools for constructing online working communities centered on the G2P domain. Through the efforts of GEN2PHEN, and through combining data with broader community‐derived knowledge, the Knowledge Centre opens up exciting possibilities for organizing, integrating, sharing, and interpreting new waves of G2P data in a collaborative fashion. Hum Mutat 32:1–8, 2011.

Finding and sharing: new approaches to registries of databases and services for the biomedical sciences

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources. Database URL: http://www.casimir.org.uk/casimir_ddf

Accreditation and attribution in data sharing

This is the authors final draft of the letter to the editor published as Nature Biotechnology, 2009, 27, pp. 984 - 985. The final version is available from http://www.nature.com/nbt/journal/v27/n11/full/nbt1109-984b.html