Article

The Human Variome Project (HVP) 2009 Forum "Towards Establishing Standards".

Genomic Disorders Research Centre, Carlton South, Victoria, Australia.
Human Mutation (Impact Factor: 5.05). 03/2010; 31(3):366-7. DOI: 10.1002/humu.21175
Source: PubMed

ABSTRACT The May 2009 Human Variome Project (HVP) Forum "Towards Establishing Standards" was a round table discussion attended by delegates from groups representing international efforts aimed at standardizing several aspects of the HVP: mutation nomenclature, description and annotation, clinical ontology, means to better characterize unclassified variants (UVs), and methods to capture mutations from diagnostic laboratories for broader distribution to the medical genetics research community. Methods for researchers to receive credit for their effort at mutation detection were also discussed.

1 Bookmark
 · 
112 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Systematic representation of information related to genetic and non-genetic variations is required to allow large scale studies, data mining and data integration, and to make it possible to reveal novel relationships between genotype and phenotype. Although lots of variation data is available it is often difficult to use due to lack of systematics. A novel ontology, Variation Ontology (VariO http://variationontology.org), was developed for annotation of effects, consequences and mechanisms of variations. In this article instructions are provided on how VariO annotations are made. The major levels for description are the three molecules, namely DNA, RNA and protein. They are further divided to four major sublevels: variation type, function, structure, and property, and further up to eight sublevels. VariO annotation summarizes existing knowledge about a variation and its effects and formalizes it so that computational analyses are efficient. The annotations should be made on as many levels as possible. VariO annotations are made in reference to normal states, which vary for each data item including e.g. reference sequences, wild type properties, and activities. Detailed instructions together with examples are provided to indicate how VariO can be used for annotation of variations and their effects. A dedicated tool has been developed for annotation and will be further developed to cover also evidence for the annotations. VariO is suitable for annotation of data in many types of databases. As several different kinds of databases are in a process of adapting VariO annotations it is important to have guidelines to guarantee consistent annotation.
    Journal of Biomedical Semantics 02/2014; 5(1):9.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Purpose:With the advent of whole-genome sequencing made clinically available, the number of incidental findings is likely to rise. The false-positive incidental findings are of particular clinical concern. We provide estimates on the size of these false-positive findings and classify them into four broad categories.Methods:Whole-genome sequences (WGS) of nine individuals were scanned with several comprehensive public annotation databases and average estimates for the number of findings. These estimates were then evaluated in the perspective of various sources of false-positive annotation errors.Results:At present there are four main sources of false-positive incidental findings: erroneous annotations, sequencing error, incorrect penetrance estimates, and multiple hypothesis testing. Of these, the first two are likely to be addressed in the near term. Conservatively, current methods deliver hundreds of false-positive incidental findings per individual.Conclusion:The burden of false-positives in whole-genome sequence interpretation threatens current capabilities to deliver clinical-grade whole-genome clinical interpretation. A new generation of population studies and retooling of the clinical decision-support approach will be required to overcome this threat.
    Genetics in medicine: official journal of the American College of Medical Genetics 02/2012; 14(4):399-404. · 3.92 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Massively parallel sequencing (MPS) has become a powerful tool for the clinical management of patients with applications in diagnosis, guidance of treatment, prediction of drug response, and carrier screening. A considerable challenge for the clinical implementation of these technologies is the management of the vast amount of sequence data generated, in particular the annotation and clinical interpretation of genomic variants. Here, we describe annotation steps that can be automated and common strategies employed for variant prioritization. The definition of best practice standards for variant annotation and prioritization is still ongoing; at present, there is limited consensus regarding an optimal clinical sequencing pipeline. We provide considerations to help define these. For the first time, clinical genetics and genomics is not limited by our ability to sequence, but our ability to clinically interpret and use genomic information in health management. We argue that the development of standardised variant annotation and interpretation approaches and software tools implementing these warrants further support. As we gain a better understanding of the significance of genomic variation through research, patients will be able to benefit from the full scope that these technologies offer. This article is protected by copyright. All rights reserved.
    Human Mutation 02/2014; · 5.05 Impact Factor

Full-text (2 Sources)

Download
10 Downloads
Available from
Sep 29, 2014