| 21. |
- Mertes, Florian, et al.
(författare)
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Targeted enrichment of genomic DNA regions for next-generation sequencing
- 2011
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Ingår i: Briefings in functional genomics. - : Oxford University Press (OUP). - 2041-2649 .- 2041-2657. ; 10:6, s. 374-386
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Forskningsöversikt (refereegranskat)abstract
- In this review, we discuss the latest targeted enrichment methods and aspects of their utilization along with second-generation sequencing for complex genome analysis. In doing so, we provide an overview of issues involved in detecting genetic variation, for which targeted enrichment has become a powerful tool. We explain how targeted enrichment for next-generation sequencing has made great progress in terms of methodology, ease of use and applicability, but emphasize the remaining challenges such as the lack of even coverage across targeted regions. Costs are also considered versus the alternative of whole-genome sequencing which is becoming ever more affordable. We conclude that targeted enrichment is likely to be the most economical option for many years to come in a range of settings.
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| 22. |
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| 24. |
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| 25. |
- Blomqvist, Mia E-L, et al.
(författare)
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Towards compendia of negative genetic association studies: an example for Alzheimer disease.
- 2006
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Ingår i: Human genetics. - : Springer Science and Business Media LLC. - 0340-6717 .- 1432-1203. ; 119:1-2, s. 29-37
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Tidskriftsartikel (refereegranskat)abstract
- Most genetic sequence variants that contribute to variability in complex human traits will have small effects that are not readily detectable with population samples typically used in genetic association studies. A potentially valuable tool in the gene discovery process is meta-analysis of the accumulated published data, but in order to be valid these require a sample of studies representative of the true genetic effect and thus hypothetically should include some positive and an abundance of negative reports. A survey of the literature on association studies for Alzheimer disease (AD) from January 2004-April 2005, identified 138 studies, 86 of which reported positive findings other than for apolipoprotein E (APOE), strongly indicative of publication bias. We report here an analysis of 62 genetic markers, tested for association with AD risk as well as for possible effects upon quantitative indices of AD severity (mini-mental state examination scores, age-at-onset, and cerebrospinal fluid (CSF) beta-amyloid (Abeta) and CSF tau proteins). Within this set, only modest signals were present that, with the exception of APOE are easily lost when corrections for multiple hypotheses are applied. In isolation, results are thus broadly negative. Genes studied encompass both novel candidates as well as several recently claimed to be associated with AD (e.g. urokinase plasminogen activator (PLAU) and acetyl-coenzyme A acetyltransferase 1 (ACAT1)). By reporting these data we hope to encourage the publication of gene compendia to guide further studies and aid future meta-analyses aimed at resolving the involvement of genes in complex human traits.
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| 26. |
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| 27. |
- Byrne, Myles, et al.
(författare)
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VarioML framework for comprehensive variation data representation and exchange
- 2012
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 13:254
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Tidskriftsartikel (refereegranskat)abstract
- Background: Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. Results: The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e. g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. Conclusions: VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.
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