Author Correction: Niche harmony search algorithm for detecting complex disease associated high-order SNP combinations (Scientific Reports (2017) DOI: 10.1038/s41598-017-11064-9);Niche harmony search algorithm for detecting complex disease associated high-order SNP combinations

Scientific Reports

Volumn 7, Issue 1, 2017, Pages

  Tuo, Shouheng ^a,b   Zhang, Junying ^a   Yuan, Xiguo ^a   He, Zongzhen ^a   Liu, Yajun ^a   Liu, Zhaowen ^a  

^a XIDIAN UNIVERSITY   (China)

^b SHAANXI UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; BIOLOGY; COMPUTER SIMULATION; GENETIC PREDISPOSITION; GENOME-WIDE ASSOCIATION STUDY; HUMAN; PROCEDURES; SINGLE NUCLEOTIDE POLYMORPHISM;

ALGORITHMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 85029535742     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-018-24597-4     Document Type: Erratum

References (63)

1. Hindorff, L. A., et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences 106, 9362-9367 (2009).
2. Manolio, T. A., et al. Finding the missing heritability of complex diseases. Nature 461, 747-753 (2009).
3. Easton, D. F., et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447, 1087-1093 (2007).
4. Fellay, J., et al. A whole-genome association study of major determinants for host control of HIV-1. Science 317, 944-947 (2007).
5. Wan, X., et al. BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies. Am. J. Hum. Genet 87, 325-340 (2010).
6. Fang, G., et al. High-Order SNP Combinations Associated with Complex Diseases: Efficient Discovery, Statistical Power and Functional Interactions. PLoS one 7, 362-366, doi: 10.1371/journal.pone.0033531 (2012).
7. Lehár, J., Krueger, A., Zimmermann, G., Borisy, A. High-order combination effects and biological robustness. Mol Syst Biol 4, 215-215 (2008).
8. Storey, J. D., Tibshirani, R. Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences 100, 9440-5 (2003).
9. Yang, C., et al. SNPHarvester: A Filtering-based Approach for Detecting Epistatic Interactions in Genome-wide Association Studies. Bioinformatics 25, 504-511 (2009).
10. Guo, et al. Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering. BMC Bioinformatics 15, 102, doi: 10.1186/1471-2105-15-102 (2014).
11. Sangseob Leem, et al. Fast detection of high-order epistatic interactions in genome-wide association studies using information theoretic measure. Computational Biology and Chemistry 50, 19-28 (2014).
12. Collins, R. L., Hu, T., Wejse, C., Sirugo, G., Williams, S. M., Moore, J. H. Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis. BioData Mining 6, 4, doi: 10.1186/1756-0381-6-4 (2013).
13. Marchini, J., Howie, B., Myers, S., McVean, G., Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39, 906-913 (2007).
14. Aflakparast, M., et al. Cuckoo search epitasis: A new method for exploring significant genetic interactions. Heredity 112, 666-674 (2014).
15. Wang, Y., et al. AntEpiSeeker: Detecting epistatic interactions for case-control studies using a two-stage ant colony optimization algorithm. BMC Res. Notes 3, 117, doi: 10.1186/1756-0500-3-117 (2010).
16. Moore, J. H., et al. Bioinformatics challenges for genome-wide association studies. Bioinformatics 26, 445-455 (2010).
17. Jing, P.-J., Shen, H.-B. MACOED: A multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies. Bioinformatics 31, 634-641 (2015).
18. Shang, J., et al. An improved opposition-based learning particle swarm optimization for the detection of SNP-SNP interactions. BioMed research international. doi: 10.1155/2015/524821 (2015).
19. Jan Christian, K., et al. High-speed exhaustive 3-locus interaction epistasis analysis on FPGAs. Journal of Computational Science 9, 131-136 (2015).
20. Yang, G., Jiang, W., Yang, Q., Yu., W. "PBOOST: A GPU based tool for parallel permutation tests in genome-wide association studies". Bioinformatics 31(9), 1460-2 (2015).
21. Yosef, N., Yakhini, Z., Tsalenko, A., Kristensen, V., Børresen-Dale, A., et al. A supervised approach for identifying discriminating genotype patterns and its application to breast cancer data. Bioinformatics 23, 91-98 (2007).
22. Wang, Z., Liu, T., Lin, Z., Hegarty, J., Koltun, W., et al. A general model for multilocus epistatic interactions in case-control studies 5. PloS One, doi: 10.1371/journal.pone.0011384 (2010).
23. Zhang, Y., Liu, J. S. Bayesian inference of epistatic interactions in case-control studies. Nature Genet 39, 1167-1173 (2007).
24. Cordell, H. J. Epistasis: What it means, what it doesn't mean, and statistical methods to detect it in humans. Hum. Mol. Genet 11, 2463-2468 (2002).
25. Cordell, H. J. Detecting gene-gene interactions that underlie human diseases. Nature Rev. Genet. 10, 392-404 (2009).
26. Wei, W. H., Hemani, G., Haley, C. S. Detecting epistasis in human complex traits. Nat Rev Genet 15, 722-33 (2014).
27. Zhao, J., Jin, L., Xiong, M. Test for interaction between two unlinked loci. Am. J. Hum. Genet 79, 831-845 (2006).
28. Zhang, Y., Zhang, J., Liu, J. S. Block-based bayesian epistasis association mapping with application to WTCCC type 1 diabetes data. Ann Appl Stat 5, 2052-2077 (2011).
29. Wang, J., et al. A Bayesian model for detection of high-order interactions among genetic variants in genome-wide association studies. BMC Genomics 16, 1011 (2015).
30. Tuo, S., Zhang, J., Yuan, X., Zhang, Y., , Liu, Z. FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm. PloS one 11. doi: 10.1371/journal.pone.0150669, (2016).
31. McDonald, J.H. G-test of goodness-of-fit. Handbook of Biological Statistics (Third ed.). Baltimore, Maryland: Sparky House Publishing. 53-58 (2014).
32. Shannon, P., Markiel, A., Ozier, O., et al. Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Research 13, 2498-2504, doi: 10.1101/gr.1239303 (2003).
33. Klein, R. J., et al. Complement factor H polymorphism in age-related macular degeneration. Science 308, 385-389 (2005).
34. Lin, W.-Y., Lee, W.-C. Incorporating prior knowledge to facilitate discoveries in a genome-wide association study on age-related macular degeneration. BMC Research Notes 3, 26, doi: 10.1186/1756-0500-3-26 (2010).
35. Tuo, J., Ning, B., Bojanowski, C. M., et al. Synergic effect of polymorphisms in ERCC6 5′ flanking region and complement factor H on age-related macular degeneration predisposition. Proceedings of the National Academy of Sciences of the United States of America 103, 9256-9261 (2006).
36. Han B, Chen X, Talebizadeh Z. FEPI-MB: Identifying SNPs-disease association using a Markov Blanket-based approach. BMC Bioinformatics 12(Suppl 12) S3. doi: 10.1186/1471-2105-12-S12-S3 (2011).
37. Sivakumaran, T. A., et al. A 32 kb Critical Region Excluding Y402H in CFH Mediates Risk for Age-Related Macular Degeneration. Urtti A, ed. PLoS ONE 6. doi: 10.1371/journal.pone.0025598 (2011).
38. Kwon M-S, Park M, Park T. IGENT: Efficient entropy based algorithm for genome-wide gene-gene interaction analysis. BMC Medical Genomics 7(Suppl 1). doi: 10.1186/1755-8794-7-S1-S6 (2014).
39. Jiang, R., et al. A random forest approach to the detection of epistatic interactions in case-control studies. BMC Bioinformatics 10, 1, doi: 10.1186/1471-2105-10-S1-S65 (2009).
40. Guo, S. T., et al. INPP4B is an oncogenic regulator in human colon cancer. Oncogene 35, 3049-3061 (2016).
41. Chen, X., Liu, C.-T., Zhang, M., Zhang, H. A forest-based approach to identifying gene and gene-gene interactions. Proceedings of the National Academy of Sciences of the United States of America 104, 19199-19203, doi: 10.1073/pnas.0709868104 (2007).
42. Wang, M., Zhang, M., Chen, X., Zhang, H. Detecting Genes and Gene-gene Interactions for Age-related Macular Degeneration with a Forest-based Approach. Statistics in biopharmaceutical research 1, 424-430, doi: 10.1198/sbr.2009.0046 (2009).
43. Shang, J., et al. CINOEDV: A co-information based method for detecting and visualizing n-order epistatic interactions. BMC Bioinformatics 17, 1, doi: 10.1186/s12859-016-1076-8 (2016).
44. Toomey, C. B., et al. Regulation of age-related macular degeneration-like pathology by complement factor H. Proceedings of the National Academy of Sciences of the United States of America 112, E3040-E3049 (2015).
45. Khan, M. A., et al. Homozygosity mapping identified a novel protein truncating mutation (p. Ser100Leufs∗24) of the BBS9 gene in a consanguineous Pakistani family with Bardet Biedl syndrome. BMC medical genetics 17, 1, doi: 10.1186/s12881-016-0271-9 (2016).
46. Chi, M. N., et al. INPP4B is upregulated and functions as an oncogenic driver through SGK3 in a subset of melanomas. Oncotarget 6, 39891-39907 (2015).
47. Vishal, M., Sharma, A., Kaurani, L., et al. Genetic association and stress mediated down-regulation in trabecular meshwork implicates MPP7 as a novel candidate gene in primary open angle glaucoma. BMC medical genomics 9(1), 1, doi: 10.1186/s12920-016-0177-6 (2016).
48. Testoni, E., et al. Somatically mutated ABL1 is an actionable and essential NSCLC survival gene. EMBO molecular medicine 8, 105-116 (2016).
49. Eckel-Passow, J. E., et al. ANKS1B is a smoking-related molecular alteration in clear cell renal cell carcinoma. BMC urology 14, 1 (2014).
50. Herberich, S. E., et al. ANKS1B Interacts with the Cerebral Cavernous Malformation Protein-1 and Controls Endothelial Permeability but Not Sprouting Angiogenesis. PloS one 10(12), e0145304, doi: 10.1371/journal.pone.0145304 (2015).
51. Bertelsen, B., et al. Intragenic deletions affecting two alternative transcripts of the IMMP2L gene in patients with Tourette syndrome. European Journal of Human Genetics 22, 1283-1289 (2014).
52. George, S. K., Jiao, Y., Bishop, C. E., Lu, B. Mitochondrial peptidase IMMP2L mutation causes early onset of age-associated disorders and impairs adult stem cell self-renewal. Aging cell 10, 584-594 (2011).
53. Geem, Z. W., Kim, J., Loganathan, G. Music-inspired optimization algorithm harmony search. Simulation 76, 60-8 (2001).
54. Yu, E. L., Suganthan, P. N. Ensemble of niching algorithms. information sciences 180, 2815-2833 (2010).
55. Ali, M. Z., Awad, N. H. A novel class of niche hybrid Cultural Algorithms for continuous engineering optimization. information sciences 267, 158-190 (2014).
56. Harremoës, P., Tusnády, G. Information divergence is more chi squared distributed than the chi squared statistic. Proceedings ISIT 2012, 538-543 (2012).
57. Quine, M. P., Robinson, J. Efficiencies of chi-square and likelihood ratio goodness-of-fit tests. Annals of Statistics 13, 727-742 (1985).
58. Harremoës, P., Vajda, I. On the Bahadur-efficient testing of uniformity by means of the entropy, IEEE Transactions on Information Theory 54, 321-331(2008).
59. Crow, J. Hardy, Weinberg and language impediments. Genetics 152, 821-825 (1999).
60. Urbanowicz, R. J., Kiralis, J., Sinnott-Armstrong, N. A., Heberling, T., Fisher, J. M., Moore, J. H. GAMETES: A fast, direct algorithm for generating pure, strict, epistatic models with random architectures. BioData mining 5, 1-14 (2012).
61. Himmelstein, et al. Evolving hard problems: Generating human genetics datasets with a complex etiology. BioData Mining 4, 21. doi: 10.1186/1756-0381-4-21. http://discovery.dartmouth.edu/model-free-data/(2011).
62. Jing, L., Horstman, B., Chen, Y. Detecting epistatic effects in association studies at a genomic level based on an ensemble approach. Bioinformatics 27, i222-i229, doi: 10.1093/bioinformatics/btr227 (2011).
63. Upton, A., Trelles, O., Cornejo-Garciá, J. A., et al. Review: High-performance computing to detect epistasis in genome scale data sets. Briefings in Bioinformatics 17(3), 368-379 (2016).