Using Online Mendelian Inheritance in Man in low- and middle-income countries.

Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders, has been used in the low- and middle-income countries largely as a tool for improving clinical care, teaching genetics and genomics, and for clinical and research analysis of next-generation sequencing. By facilitating free access to curated, updated, and comprehensive information in genetics and genomics, OMIM has led to better clinical care and research advancement in countries where clinicians and researchers in private or public hospitals and universities cannot afford to pay for other resources including journal subscriptions.

Samasy: an automated system for sample selection and robotic transfer.

Sample automation and management is increasingly important as the number and size of population-scale and high-throughput projects grow. This is particularly the case in large-scale population studies where sample size is far outpacing the commonly used 96-well plate format. To facilitate management and transfer of samples in this format, we present Samasy, a web-based application for the construction of a sample database, intuitive display of sample and batch information, and facilitation of automated sample transfer or subset. Samasy is designed with ease-of-use in mind, can be quickly set up, and runs in any web browser.

Better governance, better access: practising responsible data sharing in the METADAC governance infrastructure.

BACKGROUND: Genomic and biosocial research data about individuals is rapidly proliferating, bringing the potential for novel opportunities for data integration and use. The scale, pace and novelty of these applications raise a number of urgent sociotechnical, ethical and legal questions, including optimal methods of data storage, management and access. Although the open science movement advocates unfettered access to research data, many of the UK's longitudinal cohort studies operate systems of managed data access, in which access is governed by legal and ethical agreements between stewards of research datasets and researchers wishing to make use of them. Amongst other things, these agreements aim to respect the reasonable expectations of the research participants who provided data and samples, as expressed in the consent process. Arguably, responsible data management and governance of data and sample use are foundational to the consent process in longitudinal studies and are an important source of trustworthiness in the eyes of those who contribute data to genomic and biosocial research. METHODS: This paper presents an ethnographic case study exploring the foundational principles of a governance infrastructure for Managing Ethico-social, Technical and Administrative issues in Data ACcess (METADAC), which are operationalised through a committee known as the METADAC Access Committee. METADAC governs access to phenotype, genotype and 'omic' data and samples from five UK longitudinal studies. FINDINGS: Using the example of METADAC, we argue that three key structural features are foundational for practising responsible data sharing: independence and transparency; interdisciplinarity; and participant-centric decision-making. We observe that the international research community is proactively working towards optimising the use of research data, integrating/linking these data with routine data generated by health and social care services and other administrative data services to improve the analysis, interpretation and utility of these data. The governance of these new complex data assemblages will require a range of expertise from across a number of domains and disciplines, including that of study participants. Human-mediated decision-making bodies will be central to ensuring achievable, reasoned and responsible decisions about the use of these data; the METADAC model described in this paper provides an example of how this could be realised.

Sustaining large-scale infrastructure to promote pre-competitive biomedical research: lessons from mouse genomics.

Bio-repositories and databases for biomedical research enable the efficient community-wide sharing of reagents and data. These archives play an increasingly prominent role in the generation and dissemination of bioresources and data essential for fundamental and translational research. Evidence suggests, however, that current funding and governance models, generally short-term and nationally focused, do not adequately support the role of archives in long-term, transnational endeavours to make and share high-impact resources. Our qualitative case study of the International Knockout Mouse Consortium and the International Mouse Phenotyping Consortium examines new governance mechanisms for archive sustainability. Funders and archive managers highlight in interviews that archives need stable public funding and new revenue-generation models to be sustainable. Sustainability also requires archives, journal publishers, and funders to implement appropriate incentives, associated metrics, and enforcement mechanisms to ensure that researchers use archives to deposit reagents and data to make them publicly accessible for academia and industry alike.

Low cost, high performance processing of single particle cryo-electron microscopy data in the cloud.

The advent of a new generation of electron microscopes and direct electron detectors has realized the potential of single particle cryo-electron microscopy (cryo-EM) as a technique to generate high-resolution structures. Calculating these structures requires high performance computing clusters, a resource that may be limiting to many likely cryo-EM users. To address this limitation and facilitate the spread of cryo-EM, we developed a publicly available 'off-the-shelf' computing environment on Amazon's elastic cloud computing infrastructure. This environment provides users with single particle cryo-EM software packages and the ability to create computing clusters with 16-480+ CPUs. We tested our computing environment using a publicly available 80S yeast ribosome dataset and estimate that laboratories could determine high-resolution cryo-EM structures for $50 to $1500 per structure within a timeframe comparable to local clusters. Our analysis shows that Amazon's cloud computing environment may offer a viable computing environment for cryo-EM.

Genetic testing practices for Charcot-Marie-Tooth type 1A disease.

INTRODUCTION: Charcot-Marie-Tooth disease type 1A (CMT1A) is caused by a PMP22 gene duplication. CMT1A has a robust electrical phenotype that can be used to direct genetic testing. We compared specialty CMT center CMT1A diagnosis rates to those of outside physicians. METHODS: Charts were reviewed for 102 patients with CMT1A seen at a specialty CMT clinic between 2001 and 2009. Nerve conduction studies, family history, date of genetic testing, and type of genetic testing (single gene vs. panel) were collected. RESULTS: Although the specialty clinic ordered more PMP22 duplication testing alone beginning at an earlier year, thereby reducing costs, both the specialty clinic and outside physicians began the decade doing panel testing and ended the decade looking at only PMP22. CONCLUSIONS: Specialty centers adapt earlier to changes in testing practice than non-specialty centers. As the landscape of genetic testing changes, the algorithms for testing will also likely change.

Introduction to section III: resources for CFTR research.

This section of Cystic Fibrosis Protocols and Diagnosis focuses on resources available to facilitate the activities of the research community in the field of cystic fibrosis (CF). An overview of the protocols and resources described in subsequent chapters of this book section is provided, as well as how they can accelerate research in this area.

How to catch all those mutations--the report of the third Human Variome Project Meeting, UNESCO Paris, May 2010.

The third Human Variome Project (HVP) Meeting "Integration and Implementation" was held under UNESCO Patronage in Paris, France, at the UNESCO Headquarters May 10-14, 2010. The major aims of the HVP are the collection, curation, and distribution of all human genetic variation affecting health. The HVP has drawn together disparate groups, by country, gene of interest, and expertise, who are working for the common good with the shared goal of pushing the boundaries of the human variome and collaborating to avoid unnecessary duplication. The meeting addressed the 12 key areas that form the current framework of HVP activities: Ethics; Nomenclature and Standards; Publication, Credit and Incentives; Data Collection from Clinics; Overall Data Integration and Access-Peripheral Systems/Software; Data Collection from Laboratories; Assessment of Pathogenicity; Country Specific Collection; Translation to Healthcare and Personalized Medicine; Data Transfer, Databasing, and Curation; Overall Data Integration and Access-Central Systems; and Funding Mechanisms and Sustainability. In addition, three societies that support the goals and the mission of HVP also held their own Workshops with the view to advance disease-specific variation data collection and utilization: the International Society for Gastrointestinal Hereditary Tumours, the Micronutrient Genomics Project, and the Neurogenetics Consortium.

Genetic analysis of complex disease--a roadmap to understanding or a colossal waste of money.

Billions of dollars are being invested by public and private agencies to study the human genome, with the ultimate goal of improving the diagnosis and treatment of human genetic disease. For monogenic disease, progress has been remarkable and for many of these, genetic discoveries have led to improved diagnosis, prevention and treatment. In contrast, for the much more common, complex diseases such as diabetes and cancer, progress has been far slower. Extensive media coverage caused naïve and unrealistically high expectations, which were followed by disappointment when dramatic results were not forthcoming rapidly. In fact, however, if one correctly assesses the complexity of the problem, progress has been exceptional. Using recently developed technology and huge genetic databases, rapid progress is expected in the coming decade. Even today, these studies are providing unique insights into the pathogenesis of complex disease, and these will undoubtedly be translated into additional tangible diagnostic or therapeutic tools in the coming years.

Personal genomes in progress: from the human genome project to the personal genome project.

The cost of a diploid human genome sequence has dropped from about $70M to $2000 since 2007--even as the standards for redundancy have increased from 7x to 40x in order to improve call rates. Coupled with the low return on investment for common single-nucleotide polylmorphisms, this has caused a significant rise in interest in correlating genome sequences with comprehensive environmental and trait data (GET). The cost of electronic health records, imaging, and microbial, immunological, and behavioral data are also dropping quickly. Sharing such integrated GET datasets and their interpretations with a diversity of researchers and research subjects highlights the need for informed-consent models capable of addressing novel privacy and other issues, as well as for flexible data-sharing resources that make materials and data available with minimum restrictions on use. This article examines the Personal Genome Project's effort to develop a GET database as a public genomics resource broadly accessible to both researchers and research participants, while pursuing the highest standards in research ethics.