OVA: Integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization

Bioinformatics

Volumn 31, Issue 23, 2015, Pages 3822-3829

  Antanaviciute, Agne ^a   Watson, Christopher M ^a,b   Harrison, Sally M ^a   Lascelles, Carolina ^a   Crinnion, Laura ^a,b   Markham, Alexander F ^a   Bonthron, David T ^a   Carr, Ian M ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

^b ST JAMES S UNIVERSITY HOSPITAL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTOME;

ALGORITHM; BIOLOGICAL ONTOLOGY; BIOLOGY; DISEASES; EXOME; GENETICS; GENOTYPE; HUMAN; PHENOTYPE; PROCEDURES; SINGLE NUCLEOTIDE POLYMORPHISM;

ALGORITHMS; BIOLOGICAL ONTOLOGIES; COMPUTATIONAL BIOLOGY; DISEASE; EXOME; GENOTYPE; HUMANS; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; TRANSCRIPTOME;

EID: 84950262401     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv473     Document Type: Article

References (43)

1. Adie, E.A. et al. (2006) SUSPECTS: enabling fast and effective prioritization of positional candidates. Bioinformatics, 22, 773-774.
2. Adzhubei, I. et al. (2013) Predicting functional effect of human missense mutations using PolyPhen-2. Curr. Protoc. Hum. Genet., Chapter 7, Unit7.-20.
3. Armstrong, R.A. (2014) When to use the Bonferroni correction. Ophthalmic Physiol. Opt., 34, 502-508.
4. Ashburner, M. et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 25-29.
5. Bornigen, D. et al. (2012) An unbiased evaluation of gene prioritization tools. Bioinformatics, 28, 3081-3088.
6. Breiman, L. Random forests. Mach. Learn., 45, 5-32.
7. Britto, R. et al. (2012) GPSy: a cross-species gene prioritization system for conserved biological processes-application in male gamete development. Nucleic Acids Res, 40, W458-W465.
8. Calderone, A. et al. (2013) mentha: a resource for browsing integrated proteininteraction networks. Nat. Methods, 10, 690-691.
9. Chen, J. et al. (2009) ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res., 37, W305-W311.
10. Chen, Y. et al. (2011a) In silico gene prioritization by integrating multiple data sources. PLoS One, 6, e21137.
11. Chen, Y.A. et al. (2011b) TargetMine, an integrated data warehouse for candidate gene prioritisation and target discovery. PLoS One, 6, e17844.
12. Eronen, L. and Toivonen, H. (2012) Biomine: predicting links between biological entities using network models of heterogeneous databases. BMC Bioinformatics, 13, 119.
13. Hall, M. et al. (2009) The WEKA data mining software. ACM SIGKDD Explor. Newsl., 11, 10.
14. Jensen, L.J. et al. (2009) STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res., 37, D412-D416.
15. Kibbe, W.A. et al. (2015) Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data. Nucleic Acids Res., 43, D1071-D1078.
16. Köhler, S. et al. (2009) Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am. J. Hum. Genet., 85, 457-464.
17. Köhler, S. et al. (2013) Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research. F1000Research, 2, 30.
18. Köhler, S. et al. (2014) The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res., 42, D966-D974.
19. Kumar, P. et al. (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc., 4, 1073-1081.
20. Landrum, M.J. et al. (2014) ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res., 42, D980-D985.
21. Legaz-García, M. del C. et al. (2012) Linking genome annotation projects with genetic disorders using ontologies. J. Med. Syst., 36(Suppl 1), S11-S23.
22. Lord, P.W. et al. (2003) Investigating semantic similarity measures across the gene ontology: the relationship between sequence and annotation. Bioinformatics, 19, 1275-1283.
23. MacArthur, D.G. et al. (2012) A systematic survey of loss-of-function variants in human protein-coding genes. Science, 335, 823-828.
24. Magrane, M. and Consortium, U. (2011) UniProt Knowledgebase: a hub of integrated protein data. Database), 2011, bar-009.
25. Mazandu, G.K. and Mulder, N.J. (2012) A topology-based metric for measuring term similarity in the gene ontology. Adv. Bioinformatics, 2012, 975783.
26. Morrison, J.L. et al. (2005) GeneRank: using search engine technology for the analysis of microarray experiments. BMC Bioinformatics, 6, 233.
27. Mungall, C.J. et al. (2012) Uberon, an integrative multi-species anatomy ontology. Genome Biol., 13, R-5.
28. Perez-Iratxeta, C. et al. (2007) Update of the G2D tool for prioritization of gene candidates to inherited diseases. Nucleic Acids Res., 35, W212-W216.
29. Pesquita, C. et al. (2009a) CESSM: Collaborative Evaluation of Semantic Similarity Measures, JB2009: Challenges in Bioinformatics. 2009.
30. Pesquita, C. et al. (2008) Metrics for GO based protein semantic similarity: a systematic evaluation. BMC Bioinformatics, 9(Suppl 5), S-4.
31. Pesquita, C. et al. (2009b) Semantic similarity in biomedical ontologies. PLoS Comput. Biol., 5, e1000443.
32. Petri, V. et al. (2014) The pathway ontology-updates and applications. J. Biomed. Semantics, 5, 7.
33. Robinson, P.N. et al. (2014) Improved exome prioritization of disease genes through cross-species phenotype comparison. Genome Res., 24, 340-348.
34. Sing, T. et al. (2005) ROCR: visualizing classifier performance in R. Bioinformatics, 21, 3940-3941.
35. Seelow, D. et al. (2008) GeneDistiller-distilling candidate genes from linkage intervals. PLoS One, 3, e3874.
36. Skarnes, W.C. et al. (2011) A conditional knockout resource for the genomewide study of mouse gene function. Nature, 474, 337-342.
37. Smedley, D. et al. (2013) PhenoDigm: analyzing curated annotations to associate animal models with human diseases. Database, 2013, bat-025.
38. Smedley, D. et al. (2014) Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases. Bioinformatics, 30, 3215-3222.
39. Smith, B. et al. (2007) The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat. Biotechnol., 25, 1251-1255.
40. Smith, C.L. and Eppig, J.T. The mammalian phenotype ontology: enabling robust annotation and comparative analysis. Wiley Interdiscip. Rev. Syst. Biol. Med., 1, 390-399.
41. Subramanian, S. (2015) Using the plurality of codon positions to identify deleterious variants in human exomes. Bioinformatics, 31, 301-305.
42. Watson, C.M. et al. (2014) Robust diagnostic genetic testing using solution capture enrichment and a novel variant-filtering interface. Hum. Mutat., 35, 434-441.
43. Zhang, L. et al. (2013) PriVar: a toolkit for prioritizing SNVs and indels from next-generation sequencing data. Bioinformatics, 29, 124-125.