GESPA: Classifying nsSNPs to predict disease association

BMC Bioinformatics

Volumn 16, Issue 1, 2015, Pages

  Khurana, Jay K ^a   Reeder, Jay E ^b   Shrimpton, Antony E ^a   Thakar, Juilee ^b,c  

^a State University of New York Upstate Medical University: College of Medicine   (United States)

^b UNIVERSITY OF ROCHESTER   (United States)

^c UNIVERSITY OF ROCHESTER MEDICAL CENTER   (United States)

Author keywords

Genetic disease; Next Generation Sequencing; nsSNP prediction; Single nucleotide polymorphisms; SNP pathogenicity; SNP phenotype

Indexed keywords

BIOINFORMATICS; COMPUTATIONAL METHODS; DIGITAL STORAGE; FORECASTING; NUCLEOTIDES;

GENETIC DISEASE; NEXT-GENERATION SEQUENCING; SINGLE NUCLEOTIDE POLYMORPHISMS; SNP PATHOGENICITY; SNP PHENOTYPE;

SOFTWARE TESTING;

DNA; PROTEIN;

CHEMISTRY; DNA SEQUENCE; GENOMICS; HIGH THROUGHPUT SEQUENCING; HUMAN; INTERNET; METABOLISM; PHENOTYPE; PROCEDURES; SINGLE NUCLEOTIDE POLYMORPHISM; SOFTWARE;

DNA; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; INTERNET; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; PROTEINS; SEQUENCE ANALYSIS, DNA; SOFTWARE;

EID: 84937782715     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-015-0673-2     Document Type: Article

References (44)

1. Ramensky V, Bork P, Sunyaev S. Human non-synonymous SNPs: server and survey. Nucleic Acids Res. 2002;30(17):3894-900.
2. Kingsmore S, Saunders C. Deep sequencing of patient genomes for disease diagnosis: when will it become routine? Sci Transl Med. 2011;3:87ps23.
3. Kingsmore S, Dinwiddie D, Miller N, Soden S, Saunders C. Adopting orphans: comprehensive genetic testing of Mendelian diseases of childhood by next-generation sequencing. Expert Rev Mol Diagn. 2011;11:855-68.
4. Saiki R, Scharf S, Faloona F, Mullis K, Horn G, Erlich H, et al. Enzymatic amplification of beta-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science. 1985;230:1350-4.
5. Keller G, Huang D, Manak M. Detection of human immunodeficiency virus type 1 DNA by polymerase chain reaction amplification and capture hybridization in microtiter wells. J Clin Microbiol. 1991;29:638-41.
6. Lander E, Botstein D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics. 1994;121:185-99.
7. Chang H, Cheng Y, Chuang L, Yang C. SNP-RFLPing 2: an updated and integrated PCR-RFLP tool for SNP genotyping. BMC Bioinformatics. 2010;11:173.
8. Adzhubei I, Schmidt S, Peshkin L, Ramensky V, Gerasimova A. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7:248-9.
9. Sunyaev S, Eisenhaber F, Rodchenkov I, Eisenhaber B, Tumanyan V, Kuznetsov E. PSIC: profile extraction from sequence alignments with position-specific counts of independent observations. Protein Eng. 1999;5:387-94.
10. Ng P, Henikoff S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31:3812-4.
11. Gonzalez-Perez A, Lopez-Bigas N. Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel. Am J Hum Genet. 2011;88:440-9.
12. Li M, Kwan J, Bao S, Yang W, Ho L, Song Y, et al. Predicting mendelian disease-causing non-synonymous single nucleotide variants in exome sequencing studies. PLoS Genet. 2013;9, e1003143.
13. Zhao N, Han J, Shyu C, Korkin D. Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning. PLoS Comput Biol. 2014;10(5), e1003592.
14. Barenboim M, Masso M, Vaisman II, Jamison DC. Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers. Proteins. 2014;71:1930-39.
15. Khurana E, Fu Y, Chen J, Gerstein M. Interpretation of genomic variants using a unified biological network approach. PLoS Comput Biol. 2013;9, e1002886.
16. Lopes M, Joyce C, Ritchie G, John S, Cunningham F, Asimit J, et al. A combined functional annotation score for non-synonymous variants. Hum Hered. 2012;73:47-51.
17. Worth C, Bickerton G, Schreyer A, Forman J, Cheng T, Lee S, et al. A structural bioinformatics approach to the analysis of nonsynonymous single nucleotide polymorphisms (nsSNPs) and their relation to disease. J Bioinform Comput Biol. 2007;5:1297-318.
18. Yates C, Sternberg M. The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions. J Mol Biol. 2013;425:3949-63.
19. Chun S, Fay J. Identification of deleterious mutations within three human genomes. Genome Res. 2009;19(9):1553-61.
20. Jiang R, Yang H, Zhou L, Kuo C, et al. Sequence-based prioritization of nonsynonymous single-nucleotide polymorphisms for the study of disease mutations. Amer Journ of Hum Genet. 2007;81(2):346-60.
21. Goldstein DB, Allen A, Keebler J, Margulies E, Petrou S, Petrovski S, et al. Sequencing studies in human genetics: design and interpretation. Nat Rev Genet. 2013;14:460-70.
22. Nielsen C, Cantor M, Dubchak I, Gordon D, Wang T. Visualizing genomes: techniques and challenges. Nat Methods. 2010;7:S5-S15.
23. Henry C, Overbeek R, Xia F, Best A, Glass E, Gilbert J, et al. Connecting genotype to phenotype in the era of high-throughput sequencing. Biochem Biophys Acta. 2011;1810(10):967-77.
24. Cooper G, Shendure J. Needles in stacks of needles: finding disease-casual variants in a wealth of genomic data. Nat Rev Genet. 2011;12:628-40.
25. Bromberg Y, Rost B. SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Res. 2007;35:3823-35.
26. Mathe E, Olivier M, Kato S, Ishioka C, Hainaut P, Tavtigian S. Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods. Nucleic Acids Res. 2006;34:1317-25.
27. Sherry S, Ward M, Kholodov M, Baker J, Phan L, Smigielski E, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29:308-11.
28. Maglott D, Ostell J, Pruitt K, Tatusova T. Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 2005;33:D54-8.
29. Landrum M, Lee J, Riley G, Jang W, Rubinstein W, Church D, et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 2014;42:D980-5.
30. Benson D, Karsch-Mizrachi I, Lipman D, Ostell J, Sayers EW. GenBank. Nucleic Acids Res. 2010;38:D46-51.
31. Altshul S, Gish W, Miller W, Myers E, Lipman D. Basic local alignment search tool. J Mol Biol. 1990;215:403-10.
32. Nehrt N, Clark W, Radiovojac P, Hahn M. Testing the ortholog conjecture with comparative functional genomic data from mammals. PLoS Comput Biol. 2011;6, e1002073.
33. Kent W. BLAT--the BLAST-like alignment tool. Genome Res. 2002;12:656-64.
34. Chenna R, Sugawara H, Koike T, Lopez R, Gibson T, Higgins D, et al. Multiple sequence alignment with the Clustal series of programs. Nucleic Acids Res. 2003;31:3497-500.
35. International HapMap Consortium, Frazer K, Ballinger D, Cox D, Hinds D, Stuve L, et al. A second generation human haplotype map of over 3.1 million nsSNPs. Nature. 2007;449:851-61.
36. Wang L, Li Y, Zhou S. A bioinformatics approach for the phenotype prediction of nonsynonymous single nucleotide polymorphisms in human cytochromes P450. Drug Metab Dispos. 2009;37:977-91.
37. Choi Y, Sims G, Murphy S, Miller J, Chan A. Predicting the functional effect of amino acid substitutions and indels. PLoS ONE. 2012;7(10):e46688.
38. Henikoff S, Henikoff J. Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci USA. 1992;89(22):10915-9.
39. Kent W, Sugnet C, Furey T, Roskin K, Pringle T, Zahler A, et al. The human genome browser at UCSC. Genome Res. 2002;12:996-1006.
40. Bairoch A, Apweiler R, Wu C, Barker W, Boeckmann B, Ferro S, et al. The Universal Protein Resource (UniProt). Nucleic Acids Res. 2005;33:D154-9.
41. Capriotti E, Calabrese R, Casadio R. Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics. 2006;22:2729-34.
42. Gribskov M, McLachlan A, Eisenberg D. Profile analysis: detection of distantly related proteins. Proc Natl Acad Sci USA. 1987;84:4355-8.
43. Dobson R, Patricia B, Caulfield M, Saqi M. Predicting deleterious nsSNPs: an analysis of sequence and structural attributes. BMC Bioinformatics. 2006;7:217.
44. Care M, Needham C, Bulpitt A, Westhead D. Deleterious SNP prediction: be mindful of your training data! Bioinformatics. 2007;23:664-72.