LoFtool: A gene intolerance score based on loss-of-function variants in 60 706 individuals

Bioinformatics

Volumn 33, Issue 4, 2017, Pages 471-474

  Fadista, João ^a,b   Oskolkov, Nikolay ^b   Hansson, Ola ^b   Groop, Leif ^b,c  

^a STATENS SERUM INSTITUT   (Denmark)

^b LUND UNIVERSITY DIABETES CENTRE   (Sweden)

^c UNIVERSITY OF HELSINKI   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; GENETIC DISORDER; GENETICS; GENOMICS; HUMAN; HUMAN GENOME; LOSS OF FUNCTION MUTATION; PROCEDURES; SOFTWARE;

BRAIN; GENETIC DISEASES, INBORN; GENOME, HUMAN; GENOMICS; HUMANS; LOSS OF FUNCTION MUTATION; SOFTWARE;

EID: 85020046273     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv602     Document Type: Article

References (30)

1. Adzhubei, I. et al. (2013) Predicting functional effect of human missense mutations using PolyPhen-2. Curr. Protoc. Hum. Genet., 7, Unit7.20.
2. Allen, A.S. et al. (2013) De novo mutations in epileptic encephalopathies. Nature, 501, 217-221.
3. Blekhman, R. et al. (2008) Natural selection on genes that underlie human disease susceptibility. Curr. Biol., 18, 883-889.
4. Brown, S.D. and Moore, M.W. (2012) The International Mouse Phenotyping Consortium: past and future perspectives on mouse phenotyping. Mamm. Genome, 23, 632-640.
5. Cingolani, P. et al. (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin), 6, 80-92.
6. Franke, L. et al. (2006) Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am. J. Hum. Genet., 78, 1011-1025.
7. Fromer, M. et al. (2014) De novo mutations in schizophrenia implicate synap-tic networks. Nature, 506, 179-184.
8. GTEx Consortium. (2015) Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science, 348, 648-660.
9. Hamosh, A. et al. (2005) Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res., 33, D514-D517.
10. Karolchik, D. et al. (2014) The UCSC Genome Browser database: 2014 update. Nucleic Acids Res., 42, D764-D770.
11. Landrum, M.J. et al. (2014) ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res., 42, D980-D985.
12. Lee, H. et al. (2014) Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA, 312, 1880-1887.
13. Lee, S. et al. (2014) Rare-variant association analysis: study designs and statistical tests. Am. J. Hum. Genet., 95, 5-23.
14. Li, J. et al. (2015) Genes with de novo mutations are shared by four neuro-psychiatric disorders discovered from NPdenovo database. Mol. Psychiatry., doi: 10.1038/mp.2015.40.
15. Liu, X. et al. (2013) dbNSFP v2.0: a database of human non-synonymous SNVs and their functional predictions and annotations. Hum. Mutat., 34, E2393-E23402.
16. McLaren, W. et al. (2010) Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics, 26, 2069-2070.
17. Neale, B.M. et al. (2012) Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature, 485, 242-245.
18. Ng, P.C. and Henikoff, S. (2003) SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res., 31, 3812-3814.
19. Petrovski, S. et al. (2013) Genic intolerance to functional variation and the interpretation of personal genomes. PLoS Genet., 9, e1003709.
20. Pruitt, K.D. et al. (2009) The consensus coding sequence (CCDS) project: Identifying a common protein-coding gene set for the human and mouse genomes. Genome Res., 19, 1316-1323.
21. Rackham, O.J. et al. (2015) EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization. Nucleic Acids Res., 43, e33.
22. Samocha, K.E. et al. (2014) A framework for the interpretation of de novo mutation in human disease. Nat. Genet., 46, 944-950.
23. Soden, S.E. et al. (2014) Effectiveness of exome and genome sequencing guided by acuity of illness for diagnosis of neurodevelopmental disorders. Sci. Transl. Med., 6, 265ra168.
24. Tennessen, J.A. et al. (2012) Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science, 337, 64-69.
25. Tranchevent, L.C. et al. (2008) ENDEAVOUR update: a web resource for gene prioritization in multiple species. Nucleic Acids Res., 36, W377-W384.
26. Wang, K. et al. (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res., 38, e164.
27. Wright, C.F. et al. (2015) Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet, 385, 1305-1314.
28. Yang, Y. et al. (2014) Molecular findings among patients referred for clinical whole-exome sequencing. JAMA, 312, 1870-1879.
29. Zaidi, S. et al. (2013) De novo mutations in histone-modifying genes in congenital heart disease. Nature, 498, 220-223.
30. Zhang, X. (2014) Exome sequencing greatly expedites the progressive research of Mendelian diseases. Front. Med., 8, 42-57.