Comparing the efficacy of SNP filtering methods for identifying a single causal SNP in a known association region

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Spencer, AV ; Walters, K ; Cox, A (2014)
  • Publisher: Wiley

Genome-wide association studies have successfully identified associations between common diseases and a large number of single nucleotide polymorphisms (SNPs) across the genome. We investigate the effectiveness of several statistics, including p-values, likelihoods, genetic map distance and linkage disequilibrium between SNPs, in filtering SNPs in several disease-associated regions. We use simulated data to compare the efficacy of filters with different sample sizes and for causal SNPs with different minor allele frequencies (MAFs) and effect sizes, focusing on the small effect sizes and MAFs likely to represent the majority of unidentified causal SNPs. In our analyses, of all the methods investigated, filtering on the ranked likelihoods consistently retains the true causal SNP with the highest probability for a given false positive rate. This was the case for all the local linkage disequilibrium patterns investigated. Our results indicate that when using this method to retain only the top 5% of SNPs, even a causal SNP with an odds ratio of 1.1 and MAF of 0.08 can be retained with a probability exceeding 0.9 using an overall sample size of 50,000. © 2013 John Wiley & Sons Ltd/University College London.
  • References (30)
    30 references, page 1 of 3

    Abraham, G., Kowalczyk, A., Zobel, J. & Inouye, M. (2013) Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease. Genet Epidemiol 37, 184-195.

    Adrianto, I., Wang, S. F., Wiley, G. B., Lessard, C. J., Kelly, J. A., Adler, A. J., Glenn, S. B., Williams, A. H., Ziegler, J. T., Comeau, M. E., Marion, M. C., Wakeland, B. E., Liang, C. Y., Kaufman, K. M., Guthridge, J. M., Alarcon-Riquelme, M. E., Alarcon, G. S., Anaya, J. M., Bae, S. C., Kim, J. H., Joo, Y. B., Boackle, S. A., Brown, E. E., Petri, M. A., Ramsey-Goldman, R., Reveille, J. D., Vila, L. M., Criswell, L. A., Edberg, J. C., Freedman, B. I., Gilkeson, G. S., Jacob, C. O., James, J. A., Kamen, D. L., Kimberly, R. P., Martin, J., Merrill, J. T., Niewold, T. B., PonsEstel, B. A., Scofield, R. H., Stevens, A. M., Tsao, B. P., Vyse, T. J., Langefeld, C. D., Harley, J. B., Wakeland, E. K., Moser, K. L., Montgomery, C. G., Gaffney, P. M., Network, B. & Network, G. (2012) Association of two independent functional risk haplotypes in TNIP1 with systemic lupus erythematosus. Arthritis Rheum 64, 3695-3705.

    Ayers, K. L. & Cordell, H. J. (2010) SNP Selection in genome-wide and candidate gene studies via penalized logistic regression. Genet Epidemiol 34, 879-891.

    Barrett, J. H., Iles, M. M., Harland, M., Taylor, J. C., Aitken, J. F., Andresen, P. A., Akslen, L. A., Armstrong, B. K., Avril, M. F., Azizi, E., Bakker, B., Bergman, W., Bianchi-Scarra, G., Bressacde Paillerets, B., Calista, D., Cannon-Albright, L. A., Corda, E., Cust, A. E., Debniak, T., Duffy, D., Dunning, A. M., Easton, D. F., Friedman, E., Galan, P., Ghiorzo, P., Giles, G. G., Hansson, J., Hocevar, M., Hoiom, V., Hopper, J. L., Ingvar, C., Janssen, B., Jenkins, M. A., Jonsson, G., Kefford, R. F., Landi, G., Landi, M. T., Lang, J., Lubinski, J., Mackie, R., Malvehy, J., Martin, N. G., Molven, A., Montgomery, G. W., van Nieuwpoort, F. A., Novakovic, S., Olsson, H., Pastorino, L., Puig, S., Puig-Butille, J. A., Randerson-Moor, J., Snowden, H., Tuominen, R., VanBelle, P., van der Stoep, N., Whiteman, D. C., Zelenika, D., Han, J. L., Fang, S. Y., Lee, J. E., Wei, Q. Y., Lathrop, G. M., Gillanders, E. M., Brown, K. M., Goldstein, A. M., Kanetsky, P. A., Mann, G. J., MacGregor, S., Elder, D. E., Amos, C. I., Hayward, N. K., Gruis, N. A., Demenais, F., Bishop, J. A. N., Bishop, D. T. & Geno, M. E. L. C. (2011) Genome-wide association study identifies three new melanoma susceptibility loci. Nat Genet 43, 1108-1113.

    Camp, N. J., Parry, M., Knight, S., Abo, R., Elliott, G., Rigas, S. H., Balasubramanian, S. P., Reed, M. W. R., McBurney, H., Latif, A., Newman, W. G., Cannon-Albright, L. A., Evans, D. G. & Cox, A. (2012) Fine-mapping CASP8 risk variants in breast cancer. Cancer Epidemiol Biomarkers Prev 21, 176-181.

    Cox, A., Dunning, A. M., Garcia-Closas, M., Balasubramanian, S., Reed, M. W. R., Pooley, K. A., Scollen, S., Baynes, C., Ponder, B. A. J., Chanock, S., Lissowska, J., Brinton, L., Peplonska, B., Southey, M. C., Hopper, J. L., McCredie, M. R. E., Giles, G. G., Fletcher, O., Johnson, N., Silva, I. D., Gibson, L., Bojesen, S. E., Nordestgaard, B. G., Axelsson, C. K., Torres, D., Hamann, U., Justenhoven, C., Brauch, H., Chang-Claude, J., Kropp, S., Risch, A., Wang-Gohrke, S., Schurmann, P., Bogdanova, N., Dork, T., Fagerholm, R., Aaltonen, K., Blomqvist, C., Nevanlinna, H., Seal, S., Renwick, A., Stratton, M. R., Rahman, N., Sangrajrang, S., Hughes, D., Odefrey, F., Brennan, P., Spurdle, A. B., Chenevix-Trench, G., Beesley, J., Mannermaa, A., Hartikainen, J., Kataja, V., Kosma, V. M., Couch, F. J., Olson, J. E., Goode, E. L., Broeks, A., Schmidt, M. K., Hogervorst, F. B. L., Van't Veer, L. J., Kang, D., Yoo, K. Y., Noh, D. Y., Ahn, S. H., Wedren, S., Hall, P., Low, Y. L., Liu, J. J., Milne, R. L., Ribas, G., Gonzalez-Neira, A., Benitez, J., Sigurdson, A. J., Stredrick, D. L., Alexander, B. H., Struewing, J. P., Pharoah, P. D. P., Easton, D. F. & Kathleen Cunningham Fdn Consortium, Breast Canc Assoc, Consortium. (2007) A common coding variant in CASP8 is associated with breast cancer risk. Nat Genet 39, 352-358.

    Encode Project Consortium (2011) A user's guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol 9, e1001046.

    Fawcett, T. (2006) An introduction to ROC analysis. Pattern Recognit Lett 27, 861-874.

    Fridley, B. L., Iversen, E., Tsai, Y.-Y., Jenkins, G. D., Goode, E. L. & Sellers, T. A. (2011) A latent model for prioritization of SNPs for functional studies. PLoS One 6, e20764.

    Guan, Y. T. & Stephens, M. (2011) Bayesian variable selection regression for genome-wide association studies and other large-scale problems. Ann Appl Stat 5, 1780-1815.

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