A review of post-GWAS prioritization approaches

Frontiers in Genetics

Volumn 4, Issue DEC, 2013, Pages

  Hou, Lin ^a   Zhao, Hongyu ^a  

^a YALE UNIVERSITY   (United States)

Author keywords

DNase I hypersensitive site; EQTL; Genome wide association studies; Non coding; Prioritization

Indexed keywords

EID: 84892385595     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2013.00280     Document Type: Review

References (41)

1. Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., et al. (2010). A method and server for predicting damaging missense mutations. Nat. Methods 7, 248-249. doi: 10.1038/nmeth0410-248.
2. Becker, K. G., Barnes, K. C., Bright, T. J., and Wang, S. A. (2004). The Genetic Association Database. Nat. Genet. 36, 431-432. doi: 10.1038/ng0504-431.
3. Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., et al. (2012). Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22, 1790-1797. doi: 10.1101/gr.137323.112.
4. Cantor, R. M., Lange, K., and Sinsheimer, J. S. (2010). Prioritizing GWAS results: a review of statistical methods and recommendations for their application. Am. J. Hum. Genet. 86, 6-22. doi: 10.1016/j.ajhg.2009.11.017.
5. Chen, R., Morgan, A., Dudley, J., Deshpande, T., Li, L., Kodama, K., et al. (2008). FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease. Genome Biol. 9, R170. doi: 10.1186/gb-2008-9-12-r170.
6. Cingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., 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 6, 80-92. doi: 10.4161/fly.19695.
7. Consortium, T. E. P. (2011). A User's Guide to the Encyclopedia of DNA Elements (ENCODE). PLoS Biol. 9:e1001046. doi: 10.1371/journal.pbio.1001046.
8. Cooper, G. M., and Shendure, J. (2011). Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data. Nat. Rev. Genet. 12, 628-640. doi: 10.1038/nrg3046.
9. Fransen, K., Visschedijk, M. C., Van Sommeren, S., Fu, J. Y., Franke, L., Festen, E. A. M., et al. (2010). Analysis of SNPs with an effect on gene expression identifies UBE2L3 and BCL3 as potential new risk genes for Crohn's disease. Hum. Mol. Genet. 19, 3482-3488. doi: 10.1093/hmg/ddq264.
10. Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., et al. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. U.S.A. 106, 9362-9367. doi: 10.1073/pnas.0903103106.
11. Jostins, L., Ripke, S., Weersma, R. K., Duerr, R. H., Mcgovern, D. P., Hui, K. Y., et al. (2012). Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119-124. doi: 10.1038/nature11582.
12. Kindt, A. S. D., Navarro, P., Semple, C. A. M., and Haley, C. (2013). The genomic signature of trait-associated variants. BMC Genomics 14:108. doi: 10.1186/1471-2164-14-108.
13. Lin, D.-Y., Zeng, D., and Tang, Z.-Z. (2013). Quantitative trait analysis in sequencing studies under trait-dependent sampling. Proc. Natl. Acad. Sci. U.S.A. 110, 12247-12252. doi: 10.1073/pnas.1221713110.
14. Lv, J., Liu, H., Su, J., Wu, X., Liu, H., Li, B., et al. (2012). DiseaseMeth: a human disease methylation database. Nucleic Acids Res. 40, D1030-D1035. doi: 10.1093/nar/gkr1169.
15. MacArthur, D. G., Balasubramanian, S., Frankish, A., Huang, N., Morris, J., Walter, K., et al. (2012). A systematic survey of loss-of-function variants in human protein-coding genes. Science 335, 823-828. doi: 10.1126/science.1215040.
16. Maunakea, A. K., Chepelev, I., and Zhao, K. (2010). Epigenome mapping in normal and disease states. Circ. Res. 107, 327-339. doi: 10.1161/CIRCRESAHA.110.222463.
17. Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., et al. (2012). Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190-1195. doi: 10.1126/science.1222794.
18. McLaren, W., Pritchard, B., Rios, D., Chen, Y., Flicek, P., and Cunningham, F. (2010). Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 26, 2069-2070. doi: 10.1093/bioinformatics/btq330.
19. Merelli, I., Calabria, A., Cozzi, P., Viti, F., Mosca, E., and Milanesi, L. (2013). SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS. BMC Bioinformatics 14:S9. doi: 10.1186/1471-2105-14-S1-S9.
20. Minelli, C., De Grandi, A., Weichenberger, C. X., Gögele, M., Modenese, M., Attia, J., et al. (2013). Importance of different types of prior knowledge in selecting genome-wide findings for follow-up. Genet. Epidemiol. 37, 205-213. doi: 10.1002/gepi.21705.
21. Ng, P. C., and Henikoff, S. (2003). SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 31, 3812-3814. doi: 10.1093/nar/gkg509.
22. Ng, P. C., and Henikoff, S. (2006). Predicting the effects of amino acid substitutions on protein function. Annu. Rev. Genomics Hum. Genet. 7, 61-80. doi: 10.1146/annurev.genom.7.080505.115630.
23. Ng, S. B., Turner, E. H., Robertson, P. D., Flygare, S. D., Bigham, A. W., Lee, C., et al. (2009). Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461, 272-276. doi: 10.1038/nature08250.
24. Nicolae, D. L., Gamazon, E., Zhang, W., Duan, S., Dolan, M. E., and Cox, N. J. (2010). Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 6:e1000888. doi: 10.1371/journal.pgen.1000888.
25. Petrovski, S., Wang, Q., Heinzen, E. L., Allen, A. S., and Goldstein, D. B. (2013). Genic intolerance to functional variation and the interpretation of personal genomes. PLoS Genet. 9:e1003709. doi: 10.1371/journal.pgen.1003709.
26. Portela, A., and Esteller, M. (2010). Epigenetic modifications and human disease. Nat. Biotech. 28, 1057-1068. doi: 10.1038/nbt.1685.
27. Saccone, S. F., Bolze, R., Thomas, P., Quan, J., Mehta, G., Deelman, E., et al. (2010). SPOT: a web-based tool for using biological databases to prioritize SNPs after a genome-wide association study. Nucleic Acids Res. 38, W201-W209. doi: 10.1093/nar/gkq513.
28. Saccone, S. F., Saccone, N. L., Swan, G. E., Madden, P. A. F., Goate, A. M., Rice, J. P., et al. (2008). Systematic biological prioritization after a genome-wide association study: an application to nicotine dependence. Bioinformatics 24, 1805-1811. doi: 10.1093/bioinformatics/btn315.
29. Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., et al. (2012). De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485, 237-241. doi: 10.1038/nature10945.
30. Stenson, P. D., Ball, E. V., Mort, M., Phillips, A. D., Shiel, J. A., Thomas, N. S., et al. (2003). Human Gene Mutation Database (HGMD): 2003 update. Hum. Mutat. 21, 577-581. doi: 10.1002/humu.10212.
31. Strömberg, U., Björk, J., Vineis, P., Broberg, K., and Zeggini, E. (2009). Ranking of genome-wide association scan signals by different measures. Int. J. Epidemiol. 38, 1364-1373. doi: 10.1093/ije/dyp285.
32. Thompson, J. R., Gögele, M., Weichenberger, C. X., Modenese, M., Attia, J., Barrett, J. H., et al. (2013). SNP prioritization using a bayesian probability of association. Genet. Epidemiol. 37, 214-221. doi: 10.1002/gepi.21704.
33. Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., et al. (2012). The accessible chromatin landscape of the human genome. Nature 489, 75-82. doi: 10.1038/nature11232.
34. Tranchevent, L.-C., Capdevila, F. B., Nitsch, D., De Moor, B., De Causmaecker, P., and Moreau, Y. (2011). A guide to web tools to prioritize candidate genes. Brief. Bioinform. 12, 22-32. doi: 10.1093/bib/bbq007.
35. Trynka, G., Hunt, K. A., Bockett, N. A., Romanos, J., Mistry, V., Szperl, A., et al. (2011). Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nat. Genet. 43, 1193-1201. doi: 10.1038/ng.998.
36. Voight, B. F., Kang, H. M., Ding, J., Palmer, C. D., Sidore, C., Chines, P. S., et al. (2012). The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet. 8:e1002793. doi: 10.1371/journal.pgen.1002793.
37. Wang, K., Li, M., and Hakonarson, H. (2010). ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164. doi: 10.1093/nar/gkq603.
38. Ward, L. D., and Kellis, M. (2012a). HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930-D934. doi: 10.1093/nar/gkr917.
39. Ward, L. D., and Kellis, M. (2012b). Interpreting noncoding genetic variation in complex traits and human disease. Nat. Biotech. 30, 1095-1106. doi: 10.1038/nbt.2422.
40. Xu, B., Roos, J. L., Dexheimer, P., Boone, B., Plummer, B., Levy, S., et al. (2011). Exome sequencing supports a de novo mutational paradigm for schizophrenia. Nat. Genet. 43, 864-868. doi: 10.1038/ng.902.
41. Yuan, H.-Y., Chiou, J.-J., Tseng, W.-H., Liu, C.-H., Liu, C.-K., Lin, Y.-J., et al. (2006). FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization. Nucleic Acids Res. 34, W635-W641. doi: 10.1093/nar/gkl236.