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The Identification of Colon Cancer Susceptibility Genes by Using Genome-Wide Scans

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Book cover Cancer Susceptibility

Part of the book series: Methods in Molecular Biology ((MIMB,volume 653))

Abstract

Recent studies have indicated that in ∼35% of all colorectal cancer (CRC) cases, the CRC was inherited. Although a number of high-risk familial variants have been identified, these mutations explain <6% of CRC cases; therefore, further genome-wide scans will need to be conducted in the future. There are two popular approaches to genome-wide scans, namely linkage and association. The linkage approach utilizes several hundred markers (typically between 300 and 500 markers) throughout the genome and identifies candidate regions shared among affected family members. Candidate regions are then scrutinized for the presence of susceptibility loci. Linkage studies require no prior information and can provide new avenues for future research, but the regions identified are often large and include many candidate genes. The second and more recent approach is the genome-wide association study (GWAS) in which hundreds of thousands of markers called single nucleotide polymorphisms (SNPs) are used to identify the SNPs associated with traits of interest by employing family-based or case-control association methods. GWAS studies require no prior information and, because they use hundreds of thousands of SNPs, they can target specific candidate genes and/or narrow regions for investigation. Study design considerations, methodology, and the execution of linkage and genome-wide association studies that use both family and case-control designs are covered in this chapter.

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References

  1. Kemp, Z., Carvajal-Carmona, L., Spain, S., Barclay, E., Gorman, M., Martin, L., et al. (2006) Evidence for a colorectal cancer susceptibility locus on chromosome 3q21-q24 from a high-density SNP genome-wide linkage scan. Hum. Mol. Genet. 15, 2903–2910.

    Article  PubMed  CAS  Google Scholar 

  2. Tomlinson, I. P., Webb, E.L., Carvajal-Carmona, P., Broderick, K., Howarth, A. Pittman, M., et al. (2008). A genome-wide association study identifies colorectal cancer susceptibility loci on chromosomes 10p14 and 8q23.3. Nat. Genet. 40, 623–630.

    Article  PubMed  CAS  Google Scholar 

  3. Daley, D., Lewis, S., Platzer, P., MacMillen, M., Willis, J., Elston, R.C., et al. (2008).Identification of susceptibility genes for cancer in a genome-wide scan: results from the colon neoplasia sibling study. Am. J. Hum. Genet. 82, 723–736.

    Article  PubMed  CAS  Google Scholar 

  4. Zanke, B.W., Greenwood, C.M., Rangrej, J., Kustra, R., Tenesa, A., Farrington, S.M., et al. (2007) Genome-wide association scan identifies a colorectal cancer susceptibility locus on chromosome 8q24. Nat. Genet. 39, 989–994.

    Article  PubMed  CAS  Google Scholar 

  5. Tomlinson, I., Webb, E., Carvajal-Carmona, L., Broderick, P., Kemp, Z., Spain, S., et al. (2007) A genome-wide association scan of tag SNPs identifies a susceptibility variant for colorectal cancer at 8q24.21. Nat. Genet. 39, 984–988.

    Article  PubMed  CAS  Google Scholar 

  6. Tenesa, A., Farrington, S.M., Prendergast, J.G., Porteous, M.E., Walker, M., Haq, N., et al. (2008) Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat. Genet. 40, 631–637.

    Article  PubMed  CAS  Google Scholar 

  7. Broderick, P., Carvajal-Carmona, L., Pittman, A.M., Webb, E., Howarth, K., Rowan, A., et al. (2007) A genome-wide association study shows that common alleles of SMAD7 influence colorectal cancer risk. Nat. Genet. 39, 1315–1317.

    Article  PubMed  CAS  Google Scholar 

  8. Houlston, R.S., Webb, E., Broderick, P., Pittman, A.M., Di Bernardo, M.C., Lubbe, S., et al. (2008) Meta-analysis of genome-wide association data identifies four new susceptibility loci for colorectal cancer. Nat. Genet. 40, 1426–1435.

    Article  PubMed  CAS  Google Scholar 

  9. Djureinovic, T., Skoglund, J., Vandrovcova, J., Zhou, X.L., Kalushkova, A., Iselius, L., et al. (2006) A genome wide linkage analysis in Swedish families with hereditary non-familial adenomatous polyposis/non-hereditary non-polyposis colorectal cancer. Gut 55, 362–366.

    Article  PubMed  CAS  Google Scholar 

  10. Wiesner, G.L., Daley, D., Lewis, S., Ticknor, C., Platzer, P., Lutterbaugh, J., et al. (2003) A subset of familial colorectal neoplasia kindreds linked to chromosome 9q22.2-31.2. Proc. Natl. Acad. Sci. U.S.A. 100, 12961–12965.

    Article  PubMed  CAS  Google Scholar 

  11. Papaemmanuil, E., Carvajal-Carmona, L., Sellick, G.S., Kemp, Z., Webb, E., Spain, S., et al. (2008) Deciphering the genetics of hereditary non-syndromic colorectal cancer. Eur. J. Hum. Genet. 16, 1477–1486.

    Article  PubMed  CAS  Google Scholar 

  12. Aaltonen, L., Johns, L., Jarvinen, H., Mecklin, J.P., and Houlston, R. (2007) Explaining the familial colorectal cancer risk associated with mismatch repair (MMR)-deficient and MMR-stable tumors. Clin. Cancer Res. 13, 356–361.

    Article  PubMed  CAS  Google Scholar 

  13. Haines, J.L., and Pericak-Vance, M.A. (2006) Genetic analysis of complex diseases. Wiley-Liss, Hoboken, N.J.

    Book  Google Scholar 

  14. Thomas, D.C. (2004) Statistical methods in genetic epidemiology. Oxford University Press, Oxford, New York.

    Google Scholar 

  15. Ziegler, A., and König, I.R. (2006) A statistical approach to genetic epidemiology: concepts and applications. Wiley-VCH, Weinheim.

    Google Scholar 

  16. Khoury, M.J., Beaty, T.H., and Cohen, B.H. (1993). Fundamentals of genetic epidemiology. Oxford University Press, New York.

    Google Scholar 

  17. Lipton, L.R., Johnson, V., Cummings, C., Fisher, S., Risby, P., Eftekhar Sadat, A.T., et al. (2004) Refining the Amsterdam Criteria and Bethesda Guidelines: testing algorithms for the prediction of mismatch repair mutation status in the familial cancer clinic. J. Clin. Oncol. 22, 4934–4943.

    Article  PubMed  CAS  Google Scholar 

  18. Risch, N. (1990) Linkage strategies for genetically complex traits. II. The power of affected relative pairs. Am. J. Hum. Genet. 46, 229–241.

    PubMed  CAS  Google Scholar 

  19. Arcos-Burgos, M., and Muenke, M. (2002) Genetics of population isolates. Clin. Genet. 61, 233–247.

    Article  PubMed  CAS  Google Scholar 

  20. Heutink, P., and Oostra, B.A. (2002) Gene finding in genetically isolated populations. Hum. Mol. Genet. 11, 2507–2515.

    Article  PubMed  CAS  Google Scholar 

  21. Shifman, S., and Darvasi, A. (2001) The value of isolated populations. Nat. Genet. 28, 309–310.

    Article  PubMed  CAS  Google Scholar 

  22. Roa, B.B., Boyd, A.A., Volcik, K., and Richards, C.S. (1996). Ashkenazi Jewish population frequencies for common mutations in BRCA1 and BRCA2. Nat. Genet. 14, 185–187.

    Article  PubMed  CAS  Google Scholar 

  23. Laken, S., Petersen, G., Gruber, S., Oddoux, C., Ostrer, H., Giardiello, F., et al. (1997) Familial colorectal cancer in Askenazim due to a hypermutable tract in APC. Nat. Genet. 17, 79–83.

    Article  PubMed  CAS  Google Scholar 

  24. Yuan, Z. Q., Wong, N. Foulkes, W. D. Alpert, L. Manganaro, F. Andreutti-Zaugg, C., et al. (1999) A missense mutation in both hMSH2 and APC in an Ashkenazi Jewish HNPCC kindred: implications for clinical screening. J. Med. Genet. 36, 790–793.

    Article  PubMed  CAS  Google Scholar 

  25. Foulkes, W. D., Thiffault, I., Gruber, S., Horwitz, B.M., Hamel, N., Lee, C., et al. (2002) The founder mutation MSH2*1906G → C is an important cause of hereditary nonpolyposis colorectal cancer in the Ashkenazi Jewish population. Am. J. Hum. Genet. 71, 1395–1412.

    Article  PubMed  CAS  Google Scholar 

  26. Toledano, H., Goldberg, Y., Kedar-Barnes, I., Baris, H., Porat, R.M., Shochat, C., et al. (2008) Homozygosity of MSH2 c.1906G → C germline mutation is associated with childhood colon cancer, astrocytoma and signs of Neurofibromatosis type I. Fam. Cancer 8, 187–194.

    Article  PubMed  Google Scholar 

  27. Jaeger, E.E., Woodford-Richens, K.L. Lockett, M., Rowan, A.J., Sawyer, E.J., Heinimann, K., et al. (2003) An ancestral Ashkenazi haplotype at the HMPS/CRAC1 locus on 15q13-q14 is associated with hereditary mixed polyposis syndrome. Am. J. Hum. Genet. 72, 1261–1267.

    Article  PubMed  CAS  Google Scholar 

  28. Tomlinson, I., Rahman, N., Frayling, I., Mangion, J., Barfoot, R., Hamoudi, R., et al. (1999) Inherited susceptibility to colorectal adenomas and carcinomas: evidence for a new predisposition gene on 15q14-q22. Gastroenterology 116, 789–795.

    Article  PubMed  CAS  Google Scholar 

  29. Jaeger, E., Webb, E., Howarth, K., Carvajal-Carmona, L., Rowan, A., Broderick, P., et al. (2008) Common genetic variants at the CRAC1 (HMPS) locus on chromosome 15q13.3 influence colorectal cancer risk. Nat. Genet. 40, 26–28.

    Article  PubMed  CAS  Google Scholar 

  30. Ott, J. (1999) Analysis of human genetic linkage. Johns Hopkins University Press, Baltimore.

    Google Scholar 

  31. Elston, R.C., Buxbaum, S., Jacobs, K. B., and Olson, J. M. (2000) Haseman and Elston revisited. Genet. Epidemiol. 19, 1–17.

    Article  PubMed  CAS  Google Scholar 

  32. Kerber, R.A., Amos, C.I., Yeap, B.Y., Finkelstein, D.M., and Thomas, D.C. (2008) Design considerations in a sib-pair study of linkage for susceptibility loci in cancer. BMC Med. Genet. 9, 64.

    Article  PubMed  Google Scholar 

  33. Zhao, H., Zhang, H., and Rotter, J.I. (1997) Cost-effective sib-pair designs in the mapping of quantitative-trait loci. Am. J. Hum. Genet. 60, 1211–1221.

    PubMed  CAS  Google Scholar 

  34. Elston, R.C., Song, D., and Iyengar, S.K. (2005) Mathematical assumptions versus biological reality: myths in affected sib pair linkage analysis. Am. J. Hum. Genet. 76, 152–156.

    Article  PubMed  CAS  Google Scholar 

  35. Edwards, J.H. (2003) Sib-pairs in multifactorial disorders: the sib-similarity problem. Clin. Genet. 63, 1–9.

    Article  PubMed  CAS  Google Scholar 

  36. Zollner, S., Wen, X., Hanchard, N.A., Herbert, M.A., Ober, C., and Pritchard, J.K. (2004) Evidence for extensive transmission distortion in the human genome. Am. J. Hum. Genet. 74, 62–72.

    Article  PubMed  Google Scholar 

  37. Risch, N., and Zhang, H. (1995) Extreme discordant sib pairs for mapping quantitative trait loci in humans. Science 268, 1584–1589.

    Article  PubMed  CAS  Google Scholar 

  38. Spielman, R.S., McGinnis R.E., and Ewens. W.J. (1993) Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am. J. Hum. Genet. 52, 506–516.

    PubMed  CAS  Google Scholar 

  39. Rabinowitz, D., and Laird, N. (2000) A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum. Hered. 50, 211–223.

    Article  PubMed  CAS  Google Scholar 

  40. Lange, C., and Laird, N.M. (2002) Power calculations for a general class of family-based association tests: dichotomous traits. Am. J. Hum. Genet. 71, 575–584.

    Article  PubMed  CAS  Google Scholar 

  41. Lange, C., and Laird, N.M. (2002) On a general class of conditional tests for family-based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations. Genet. Epidemiol. 23, 165–180.

    Article  PubMed  Google Scholar 

  42. Lange, C., DeMeo, D.L., and Laird, N.M. (2002) Power and design considerations for a general class of family-based association tests: quantitative traits. Am. J. Hum. Genet. 71, 1330–1341.

    Article  PubMed  CAS  Google Scholar 

  43. Lange, C., DeMeo, D. Silverman, E.K. Weiss, S.T., and Laird, N.M. (2003) Using the noninformative families in family-based association tests: a powerful new testing strategy. Am. J. Hum. Genet. 73, 801–811.

    Article  PubMed  CAS  Google Scholar 

  44. Lange, C., Lyon, H., DeMeo, D., Raby, B., Silverman, E.K., and Weiss, S.T. (2003) A new powerful non-parametric two-stage approach for testing multiple phenotypes in family-based association studies. Hum. Hered. 56, 10–17.

    Article  PubMed  Google Scholar 

  45. Lange, C., Silverman, E.K., Xu, X., Weiss, S.T., and Laird, N.M. 2003. A multivariate family-based association test using generalized estimating equations: FBAT-GEE. Biostatistics 4, 195–206.

    Article  PubMed  Google Scholar 

  46. Lange, C., DeMeo, D., Silverman, E.K., Weiss, S.T., and Laird, N.M. (2004) PBAT: tools for family-based association studies. Am. J. Hum. Genet. 74, 367–369.

    Article  PubMed  Google Scholar 

  47. Laird, N.M., Horvath, S., and Xu, X. (2000) Implementing a unified approach to family-based tests of association. Genet. Epidemiol. 19, Suppl 1: S36–S42.

    Article  PubMed  Google Scholar 

  48. Horvath, S., Xu, X., Lake, S.L., Silverman, E.K., Weiss, S.T., and Laird, N.M. (2004) Family-based tests for associating haplotypes with general phenotype data: application to asthma genetics. Genet. Epidemiol. 26, 61–69.

    Article  PubMed  Google Scholar 

  49. Spielman, R.S., and Ewens, W.J. (1998) A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. Am. J. Hum. Genet. 62, 450–458.

    Article  PubMed  CAS  Google Scholar 

  50. Risch, N., and Merikangas, K. (1996) The future of genetic studies of complex human diseases. Science 273, 1516–1517.

    Article  PubMed  CAS  Google Scholar 

  51. Burton, PR., Clayton, D.G., Cardon, L.R., Craddock, N., Deloukas, P., Duncanson, A., et al. 2007. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678.

    Article  CAS  Google Scholar 

  52. Price, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick, N.A., and Reich, D. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909.

    Article  PubMed  CAS  Google Scholar 

  53. Purcell, S., Cherny, S.S., and Sham, P. C. (2003) Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19, 149–150.

    Article  PubMed  CAS  Google Scholar 

  54. Menashe, I., Rosenberg, P.S., and Chen, B.E. (2008) PGA: power calculator for case-control genetic association analyses. BMC Genet. 9, 36.

    Article  PubMed  Google Scholar 

  55. Ploughman, L.M., and Boehnke, M. 1989. Estimating the power of a proposed linkage study for a complex genetic trait. Am. J. Hum. Genet. 44, 543–551.

    PubMed  CAS  Google Scholar 

  56. Boehnke, M. (1986) Estimating the power of a proposed linkage study: a practical computer simulation approach. Am. J. Hum. Genet. 39, 513–527.

    PubMed  CAS  Google Scholar 

  57. Terwilliger, J.D., and Ott, J. (1994) Handbook of human genetic linkage. Johns Hopkins University Press, Baltimore.

    Google Scholar 

  58. (2009) S.A.G.E. Statistical Analysis for Genetic Epidemiology.

    Google Scholar 

  59. Whittaker, J.C., and Lewis, C.M. (1999) Power comparisons of the transmission/disequilibrium test and sib-transmission/disequilibrium-test statistics. Am. J. Hum. Genet. 65, 578–580.

    Article  PubMed  CAS  Google Scholar 

  60. Knapp, M. (1999) A note on power approximations for the transmission/disequilibrium test. Am. J. Hum. Genet. 64, 1177–1185.

    Article  PubMed  CAS  Google Scholar 

  61. Knapp, M. (1999) The transmission/disequilibrium test and parental-genotype reconstruction: the reconstruction-combined transmission/disequilibrium test. Am. J. Hum. Genet. 64, 861–870.

    Article  PubMed  CAS  Google Scholar 

  62. Passarge, E. (2002) Dissecting Hirschsprung disease. Nat. Genet. 31, 11–12.

    PubMed  CAS  Google Scholar 

  63. Knowler, W.C., Williams, R.C., Pettitt, D.J., and Steinberg, A.G. (1988) Gm3;5,13,14 and type 2 diabetes mellitus: an association in American Indians with genetic admixture. Am. J. Hum. Genet. 43, 520–526.

    PubMed  CAS  Google Scholar 

  64. Clayton, D.G., Walker, N.M., Smyth, D.J., Pask, R., Cooper, J.D., Maier, L.M., et al. (2005) Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat. Genet. 37, 1243–1246.

    Article  PubMed  CAS  Google Scholar 

  65. Devlin, B., and Roeder, K. (1999) Genomic control for association studies. Biometrics 55, 997–1004.

    Article  PubMed  CAS  Google Scholar 

  66. Price, A. L., Butler, J., Patterson, N., Capelli, C., Pascali, V.L., Scarnicci, F., et al. (2008) Discerning the ancestry of European Americans in genetic association studies. PLoS Genet. 4, e236.

    Article  PubMed  Google Scholar 

  67. Nelis, M., Esko, T., Magi, R., Zimprich, F., Zimprich, A., Toncheva, D., et al. (2009). Genetic structure of Europeans: a view from the North-East. PLoS One 4, e5472.

    Article  PubMed  Google Scholar 

  68. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A., Bender, D., et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575.

    Article  PubMed  CAS  Google Scholar 

  69. Ziegler, A., Konig, I.R., and Thompson, J.R. (2008) Biostatistical aspects of genome-wide association studies. Biom. J. 50, 8–28.

    Article  PubMed  Google Scholar 

  70. Cunningham, J.M., Sellers, T.A., Schildkraut, J.M., Fredericksen, Z.S., Vierkant, R.A., Kelemen, L.E., et al. (2008). Performance of amplified DNA in an Illumina GoldenGate BeadArray assay. Cancer Epidemiol. Biomarkers Prev. 17, 1781–1789.

    Article  PubMed  CAS  Google Scholar 

  71. Berthier-Schaad, Y., Kao, W.H., Coresh, J., Zhang, L., Ingersoll, R.G., Stephens, R., et al. (2007) Reliability of high-throughput genotyping of whole genome amplified DNA in SNP genotyping studies. Electrophoresis 28, 2812–2817.

    Article  PubMed  CAS  Google Scholar 

  72. Abecasis, G.R., Cherny, S.S., Cookson, W.O., and Cardon, L.R. (2001) GRR: graphical representation of relationship errors. Bioinformatics 17, 742–743.

    Article  PubMed  CAS  Google Scholar 

  73. International HapMap Consortium. (2005) A haplotype map of the human genome. Nature 437, 1299–1320.

    Article  Google Scholar 

  74. Samani, N. J., Erdmann, J., Hall, A.S., Hengstenberg, C., Mangino, M., Mayer, B., et al. (2007) Genomewide association analysis of coronary artery disease. N. Engl. J. Med. 357, 443–453.

    Article  PubMed  CAS  Google Scholar 

  75. Dudbridge, F. (2008) Likelihood-based association analysis for nuclear families and unrelated subjects with missing genotype data. Hum. Hered. 66, 87–98.

    Article  PubMed  Google Scholar 

  76. Marchini, J., Cardon, L.R., Phillips, M.S., and Donnelly, P. (2004) The effects of human population structure on large genetic association studies. Nat. Genet. 36, 512–517.

    Article  PubMed  CAS  Google Scholar 

  77. de Bakker, P.I., Yelensky, R., Pe’er, I., Gabriel, S.B., Daly, M.J., and Altshuler, D. (2005) Efficiency and power in genetic association studies. Nat. Genet. 37, 1217–1223.

    Article  PubMed  Google Scholar 

  78. Cordell, H.J. (2009) Genome-wide association studies: detecting gene–gene interactions that underlie human diseases. Nat. Rev. Genet. 10, 392–404.

    Article  PubMed  CAS  Google Scholar 

  79. Wacholder, S., Chanock, S., Garcia-Closas, M., El Ghormli, L., and Rothman, N. (2004) Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J. Natl. Cancer Inst. 96, 434–442.

    Article  PubMed  Google Scholar 

  80. Hochberg, Y.B.A.Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Stat. Soc. 57, 289–300.

    Google Scholar 

  81. Howie, B.N., Donnelly, P., and Marchini, J. (2009) A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529.

    Article  PubMed  Google Scholar 

  82. Aschard, H., Bouzigon, E., Corda, E., Ulgen, A., Dizier, M.H., Gormand, F., et al. (2009) Sex-specific effect of IL9 polymorphisms on lung function and polysensitization. Genes Immun. 10, 559–565.

    Article  PubMed  CAS  Google Scholar 

  83. Browning, B.L., and Browning, S.R. (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 84, 210–223.

    Article  PubMed  CAS  Google Scholar 

  84. Marchini, J., Howie, B., Myers, S., McVean, G., and Donnelly, P. (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913.

    Article  PubMed  CAS  Google Scholar 

  85. Scheet, P., and Stephens, M. (2006) A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 78, 629–644.

    Article  PubMed  CAS  Google Scholar 

  86. Pei, Y.F., Li, J., Zhang, L., Papasian, C.J., and Deng, H.W. (2008) Analyses and comparison of accuracy of different genotype imputation methods. PLoS One 3, e3551.

    Article  PubMed  Google Scholar 

  87. Devlin, B., Bacanu, S.A., and Roeder, K. (2004) Genomic Control to the extreme. Nat. Genet. 36, 1129–1130; author reply 1131.

    Article  PubMed  CAS  Google Scholar 

  88. Tintle, N.L., Gordon, D., McMahon F.J., and Finch, S.J. (2007) Using duplicate genotyped data in genetic analyses: testing association and estimating error rates. Stat. Appl. Genet. Mol. Biol. 6, Article 4.

    Google Scholar 

  89. Huang, L., Li, Y., Singleton, A.B., Hardy, J.A., Abecasis, G., Rosenberg, N.A., et al. (2009) Genotype-imputation accuracy across worldwide human populations. Am. J. Hum Genet. 84, 235–250.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The author would like to thank Veronica Yakoleff for editing the manuscript.

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  1. Department of Medicine, St. Paul’s Hospital, University of British Columbia, Vancouver, BC, Canada

    Denise Daley

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  1. , School of Clinical Laboratory Sciences, University of Manchester, Oxford Road, Manchester, M13 9PT, United Kingdom

    Michelle Webb

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Daley, D. (2010). The Identification of Colon Cancer Susceptibility Genes by Using Genome-Wide Scans. In: Webb, M. (eds) Cancer Susceptibility. Methods in Molecular Biology, vol 653. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-759-4_1

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  • DOI: https://doi.org/10.1007/978-1-60761-759-4_1

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