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- Abel, Olubunmi, et al.
(författare)
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ALSoD : A user-friendly online bioinformatics tool for amyotrophic lateral sclerosis genetics
- 2012
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Ingår i: Human Mutation. - Hoboken, NJ : Wiley-Blackwell. - 1059-7794 .- 1098-1004. ; 33:9, s. 1345-1351
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Tidskriftsartikel (refereegranskat)abstract
- Amyotrophic lateral sclerosis (ALS) is the commonest adult onset motor neuron disease, with a peak age of onset in the seventh decade. With advances in genetic technology, there is an enormous increase in the volume of genetic data produced, and a corresponding need for storage, analysis, and interpretation, particularly as our understanding of the relationships between genotype and phenotype mature. Here, we present a system to enable this in the form of the ALS Online Database (ALSoD at http://alsod.iop.kcl.ac.uk), a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD. Hum Mutat 33:1345-1351, 2012. (c) 2012 Wiley Periodicals, Inc.
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| 2. |
- Abel, Olubunmi, et al.
(författare)
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Credibility analysis of putative disease-causing genes using bioinformatics
- 2013
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:6, s. e64899-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genetic studies are challenging in many complex diseases, particularly those with limited diagnostic certainty, low prevalence or of old age. The result is that genes may be reported as disease-causing with varying levels of evidence, and in some cases, the data may be so limited as to be indistinguishable from chance findings. When there are large numbers of such genes, an objective method for ranking the evidence is useful. Using the neurodegenerative and complex disease amyotrophic lateral sclerosis (ALS) as a model, and the disease-specific database ALSoD, the objective is to develop a method using publicly available data to generate a credibility score for putative disease-causing genes.Methods: Genes with at least one publication suggesting involvement in adult onset familial ALS were collated following an exhaustive literature search. SQL was used to generate a score by extracting information from the publications and combined with a pathogenicity analysis using bioinformatics tools. The resulting score allowed us to rank genes in order of credibility. To validate the method, we compared the objective ranking with a rank generated by ALS genetics experts. Spearman's Rho was used to compare rankings generated by the different methods.Results: The automated method ranked ALS genes in the following order: SOD1, TARDBP, FUS, ANG, SPG11, NEFH, OPTN, ALS2, SETX, FIG4, VAPB, DCTN1, TAF15, VCP, DAO. This compared very well to the ranking of ALS genetics experts, with Spearman's Rho of 0.69 (P = 0.009).Conclusion: We have presented an automated method for scoring the level of evidence for a gene being disease-causing. In developing the method we have used the model disease ALS, but it could equally be applied to any disease in which there is genotypic uncertainty.
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