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Table of Contents
Vol. 71, No. 4, 2011
Issue release date: September 2011
Section title: Original Paper
Free Access
Hum Hered 2011;71:256–266
(DOI:10.1159/000329467)

PSEUDOMARKER: A Powerful Program for Joint Linkage and/or Linkage Disequilibrium Analysis on Mixtures of Singletons and Related Individuals

Hiekkalinna T.a, b · Schäffer A.A.c · Lambert B.d · Norrgrann P.a, b · Göring H.H.H.e · Terwilliger J.D.a, f–i
aInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, and bNational Institute for Health and Welfare, Unit of Public Health Genomics, Helsinki, Finland; cComputational Biology Branch, National Center for Biotechnology Information, NIH, DHHS, Bethesda, Md., dDepartment of Anthropology, Pennsylvania State University, State College, Pa., eDepartment of Genetics, Texas Biomedical Research Institute, San Antonio, Tex., Departments of fPsychiatry and gGenetics and Development, and hColumbia Genome Center, Columbia University, and iDivision of Medical Genetics, New York State Psychiatric Institute, New York, N.Y., USA
email Corresponding Author

Abstract

A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER’s advantages over other packages by example.

© 2011 S. Karger AG, Basel


  

Key Words

  • Computer software
  • Family-based association
  • Genome-wide association
  • Likelihood methods
  • Linkage analysis
  • Linkage disequilibrium
  • Study design

References

  1. Blangero J: Localization and identification of human quantitative trait loci: king harvest has surely come. Curr Opin Genet Dev 2004;14:233–240.
  2. Terwilliger JD, Göring HH: Update to Terwilliger and Göring’s ‘Gene mapping in the 20th and 21st centuries’ (2000): Gene mapping when rare variants are common and common variants are rare. Hum Biol 2009;81:729–733.

    External Resources

  3. Risch N, Merikangas K: The future of genetic studies of complex human diseases. Science 1996;273:1516–1517.
  4. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors IV: joint pseudomarker analysis of linkage and/or linkage disequilibrium on a mixture of pedigrees and singletons when the mode of inheritance cannot be accurately specified. Am J Hum Genet 2000;66:1310–1327.
  5. Terwilliger JD, Göring HH: Gene mapping in the 20th and 21st centuries: statistical methods, data analysis, and experimental design. Hum Biol 2000;72:63–132.
  6. Mein CA, Esposito L, Dunn MG, Johnson GC, Timms AE, Goy JV, Smith AN, Sebag-Montefiore L, Merriman ME, Wilson AJ, Pritchard LE, Cucca F, Barnett AH, Bain SC, Todd JA: A search for type 1 diabetes susceptibility genes in families from the United Kingdom. Nat Genet 1998;19:297–300.
  7. Laird NM, Horvath S, Xu X: Implementing a unified approach to family-based tests of association. Genet Epidemiol 2000;19(suppl 1):S36–S42.
  8. Rabinowitz D, Laird N: A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum Hered 2000;50:211–223.
  9. Abecasis GR, Cardon LR, Cookson WO: A general test of association for quantitative traits in nuclear families. Am J Hum Genet 2000;66:279–292.
  10. Abecasis GR, Cookson WO, Cardon LR: Pedigree tests of transmission disequilibrium. Eur J Hum Genet 2000;8:545–551.
  11. Clayton D: A generalization of the transmission/disequilibrium test for uncertain-haplotype transmission. Am J Hum Genet 1999;65:1170–1177.
  12. Dudbridge F: Likelihood-based association analysis for nuclear families and unrelated subjects with missing genotype data. Hum Hered 2008;66:87–98.
  13. Allen-Brady K, Wong J, Camp NJ: Pedgenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size. BMC Bioinformatics 2006;7:209.
  14. Hasstedt SJ: A mixed-model likelihood approximation on large pedigrees. Comput Biomed Res 1982;15:295–307.
  15. McKenzie CA, Julier C, Forrester T, McFarlane-Anderson N, Keavney B, Lathrop GM, Ratcliffe PJ, Farrall M: Segregation and linkage analysis of serum angiotensin I-converting enzyme levels: evidence for two quantitative-trait loci. Am J Hum Genet 1995;57:1426–1435.
  16. Lathrop GM, Lalouel JM: Easy calculations of LOD scores and genetic risks on small computers. Am J Hum Genet 1984;36:460–465.
  17. Hellsten E, Vesa J, Speer MC, Makela TP, Jarvela I, Alitalo K, Ott J, Peltonen L: Refined assignment of the infantile neuronal ceroid lipofuscinosis (INCL, CLN1) locus at 1p32: Incorporation of linkage disequilibrium in multipoint analysis. Genomics 1993;16:720–725.
  18. Tienari PJ, Terwilliger JD, Ott J, Palo J, Peltonen L: Two-locus linkage analysis in multiple sclerosis (MS). Genomics 1994;19:320–325.
  19. Li M, Boehnke M, Abecasis GR: Joint modeling of linkage and association: Identifying SNPs responsible for a linkage signal. Am J Hum Genet 2005;76:934–949.
  20. Li M, Boehnke M, Abecasis GR: Efficient study designs for test of genetic association using sibship data and unrelated cases and controls. Am J Hum Genet 2006;78:778–792.
  21. Lange K, Cantor R, Horvath S, Perola M, Sabatti C, Sinsheimer J, Sobel E: Mendel version 4.0: a complete package for the exact genetic analysis of discrete traits in pedigree and population data sets. Am J Hum Genet 2001;69(suppl):504.

    External Resources

  22. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors II: marker-locus genotyping errors modeled with hypercomplex recombination fractions. Am J Hum Genet 2000;66:1107–1118.
  23. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors I: complex-valued recombination fractions and complex phenotypes. Am J Hum Genet 2000;66:1095–1106.
  24. Blackwelder WC, Elston RC: A comparison of sib-pair linkage tests for disease susceptibility loci. Genet Epidemiol 1985;2:85–97.
  25. Nordheim EV, O’Malley DM, Chow SC: On the performance of a likelihood ratio test for genetic linkage. Biometrics 1984;40:785–790.

    External Resources

  26. Penrose LS: The detection of autosomal linkage in data which consist of pairs of brothers and sisters of unspecified parentage. Ann of Eug 1935;133–138.

    External Resources

  27. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors III: marker loci and their map as nuisance parameters. Am J Hum Genet 2000;66:1298–1309.
  28. Falk CT, Rubinstein P: Haplotype relative risks: an easy reliable way to construct a proper control sample for risk calculations. Ann Hum Genet 1987;51:227–233.
  29. Terwilliger JD, Ott J: A haplotype-based ‘haplotype relative risk’ approach to detecting allelic associations. Hum Hered 1992;42:337–346.
  30. Spielman RS, McGinnis RE, Ewens WJ: Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet 1993;52:506–516.
  31. Terwilliger JD: On the resolution and feasibility of genome scanning approaches. Adv Genet 2001;42:351–391.
  32. Cottingham RW Jr, Idury RM, Schäffer AA: Faster sequential genetic linkage computations. Am J Hum Genet 1993;53:252–263.
  33. Lathrop GM, Lalouel JM, Julier C, Ott J: Strategies for multilocus linkage analysis in humans. Proc Natl Acad Sci USA 1984;81:3443–3446.
  34. Lathrop GM, Lalouel JM, White RL: Construction of human linkage maps: likelihood calculations for multilocus linkage analysis. Genet Epidemiol 1986;3:39–52.
  35. Schäffer AA, Gupta SK, Shriram K, Cottingham RW Jr: Avoiding recomputation in linkage analysis. Hum Hered 1994;44:225–237.
  36. Simard LR, Prescott G, Rochette C, Morgan K, Lemieux B, Mathieu J, Melancon SB, Vanasse M: Linkage disequilibrium analysis of childhood-onset spinal muscular atrophy (SMA) in the French-Canadian population. Hum Mol Genet 1994;3:459–463.
  37. Ott J: Estimation of the recombination fraction in human pedigrees: efficient computation of the likelihood for human linkage studies. Am J Hum Genet 1974;26:588–597.
  38. Elston RC, Stewart J: A general model for the genetic analysis of pedigree data. Hum Hered 1971;21:523–542.
  39. Lalouel JM: GEMINI – A Computer Program for Optimization of a Nonlinear Function. Department of Medical Biophysics and Computing, University of Utah, Salt Lake City, 1979.
  40. Torczon V: On the convergence of the multidirectional search algorithm. SIAM J Optim 1991;1:123–145.

    External Resources

  41. Terwilliger JD, Ott J: Handbook of Human Genetic Linkage. Johns Hopkins University Press, Baltimore, 1994.
  42. Mukhopadhyay N, Almasy L, Schroeder M, Mulvihill WP, Weeks DE: Mega2, a data-handling program for facilitating genetic linkage and association analyses. Am J Hum Genet 1999;65:A436.

    External Resources

  43. Becker A, Geiger D, Schäffer AA: Automatic selection of loop breakers for genetic linkage analysis. Hum Hered 1998;48:49–60.
  44. Dennis JE Jr, Torczon V: Direct search methods on parallel machines. SIAM J Optim 1991;1:448–474.

    External Resources

  45. Wessman M, Kallela M, Kaunisto MA, Marttila P, Sobel E, Hartiala J, Oswell G, Leal SM, Papp JC, Hämäläinen E, Broas P, Joslyn G, Hovatta I, Hiekkalinna T, Kaprio J, Ott J, Cantor RM, Zwart JA, Ilmavirta M, Havanka H, Färkkilä M, Peltonen L, Palotie A: A susceptibility locus for migraine with aura, on chromosome 4q24. Am J Hum Genet 2002;70:652–662.
  46. Kaunisto MA, Tikka PJ, Kallela M, Leal SM, Papp JC, Korhonen A, Hämäläinen E, Harno H, Havanka H, Nissilä M, Säkö E, Ilmavirta M, Kaprio J, Färkkilä M, Ophoff RA, Palotie A, Wessman M: Chromosome 19p13 loci in Finnish migraine with aura families. Am J Med Genet B Neuropsychiatr Genet 2005;132:85–89.
  47. Ekelund J, Hovatta I, Parker A, Paunio T, Varilo T, Martin R, Suhonen J, Ellonen P, Chan G, Sinsheimer JS, Sobel E, Juvonen H, Arajärvi R, Partonen T, Suvisaari J, Lönnqvist J, Meyer J, Peltonen L: Chromosome 1 loci in Finnish schizophrenia families. Hum Mol Genet 2001;10:1611–1617.
  48. Hiekkalinna T, Göring HHH, Lambert BW, Weiss KM, Norrgrann P, Schäffer AA, Terwilliger JD: On the statistical properties of family-based association tests in datasets containing both pedigrees and unrelated case-control samples. Under review 2011.
  49. Lambert BW, Terwilliger JD, Weiss KM: ForSim: a tool for exploring the genetic architecture of complex traits with controlled truth. Bioinformatics 2008;24:1821–1822.
  50. Ott J: Computer-simulation methods in human linkage analysis. Proc Natl Acad Sci USA 1989;86:4175–4178.
  51. Weeks DE, Ott J, Lathrop GM: SLINK: a general simulation program for linkage analysis. Am J Hum Genet 1990;A204.
  52. Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES: Parametric and nonparametric linkage analysis: a unified multipoint approach. Am J Hum Genet 1996;58:1347–1363.
  53. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC: PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–575.

  

Author Contacts

Tero Hiekkalinna
National Institute for Health and Welfare (THL)
Public Health Genomics Unit, Biomedicum Helsinki
PO Box 104, FI–00251 Helsinki (Finland)
Tel. +358 20 610 8283, E-Mail tero.hiekkalinna@helsinki.fi

  

Article Information

Received: February 7, 2011
Accepted after revision: May 17, 2011
Published online: July 28, 2011
Number of Print Pages : 11
Number of Figures : 1, Number of Tables : 4, Number of References : 53

  

Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 71, No. 4, Year 2011 (Cover Date: September 2011)

Journal Editor: Devoto M. (Philadelphia, Pa./Rome)
ISSN: 0001-5652 (Print), eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


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References

  1. Blangero J: Localization and identification of human quantitative trait loci: king harvest has surely come. Curr Opin Genet Dev 2004;14:233–240.
  2. Terwilliger JD, Göring HH: Update to Terwilliger and Göring’s ‘Gene mapping in the 20th and 21st centuries’ (2000): Gene mapping when rare variants are common and common variants are rare. Hum Biol 2009;81:729–733.

    External Resources

  3. Risch N, Merikangas K: The future of genetic studies of complex human diseases. Science 1996;273:1516–1517.
  4. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors IV: joint pseudomarker analysis of linkage and/or linkage disequilibrium on a mixture of pedigrees and singletons when the mode of inheritance cannot be accurately specified. Am J Hum Genet 2000;66:1310–1327.
  5. Terwilliger JD, Göring HH: Gene mapping in the 20th and 21st centuries: statistical methods, data analysis, and experimental design. Hum Biol 2000;72:63–132.
  6. Mein CA, Esposito L, Dunn MG, Johnson GC, Timms AE, Goy JV, Smith AN, Sebag-Montefiore L, Merriman ME, Wilson AJ, Pritchard LE, Cucca F, Barnett AH, Bain SC, Todd JA: A search for type 1 diabetes susceptibility genes in families from the United Kingdom. Nat Genet 1998;19:297–300.
  7. Laird NM, Horvath S, Xu X: Implementing a unified approach to family-based tests of association. Genet Epidemiol 2000;19(suppl 1):S36–S42.
  8. Rabinowitz D, Laird N: A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum Hered 2000;50:211–223.
  9. Abecasis GR, Cardon LR, Cookson WO: A general test of association for quantitative traits in nuclear families. Am J Hum Genet 2000;66:279–292.
  10. Abecasis GR, Cookson WO, Cardon LR: Pedigree tests of transmission disequilibrium. Eur J Hum Genet 2000;8:545–551.
  11. Clayton D: A generalization of the transmission/disequilibrium test for uncertain-haplotype transmission. Am J Hum Genet 1999;65:1170–1177.
  12. Dudbridge F: Likelihood-based association analysis for nuclear families and unrelated subjects with missing genotype data. Hum Hered 2008;66:87–98.
  13. Allen-Brady K, Wong J, Camp NJ: Pedgenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size. BMC Bioinformatics 2006;7:209.
  14. Hasstedt SJ: A mixed-model likelihood approximation on large pedigrees. Comput Biomed Res 1982;15:295–307.
  15. McKenzie CA, Julier C, Forrester T, McFarlane-Anderson N, Keavney B, Lathrop GM, Ratcliffe PJ, Farrall M: Segregation and linkage analysis of serum angiotensin I-converting enzyme levels: evidence for two quantitative-trait loci. Am J Hum Genet 1995;57:1426–1435.
  16. Lathrop GM, Lalouel JM: Easy calculations of LOD scores and genetic risks on small computers. Am J Hum Genet 1984;36:460–465.
  17. Hellsten E, Vesa J, Speer MC, Makela TP, Jarvela I, Alitalo K, Ott J, Peltonen L: Refined assignment of the infantile neuronal ceroid lipofuscinosis (INCL, CLN1) locus at 1p32: Incorporation of linkage disequilibrium in multipoint analysis. Genomics 1993;16:720–725.
  18. Tienari PJ, Terwilliger JD, Ott J, Palo J, Peltonen L: Two-locus linkage analysis in multiple sclerosis (MS). Genomics 1994;19:320–325.
  19. Li M, Boehnke M, Abecasis GR: Joint modeling of linkage and association: Identifying SNPs responsible for a linkage signal. Am J Hum Genet 2005;76:934–949.
  20. Li M, Boehnke M, Abecasis GR: Efficient study designs for test of genetic association using sibship data and unrelated cases and controls. Am J Hum Genet 2006;78:778–792.
  21. Lange K, Cantor R, Horvath S, Perola M, Sabatti C, Sinsheimer J, Sobel E: Mendel version 4.0: a complete package for the exact genetic analysis of discrete traits in pedigree and population data sets. Am J Hum Genet 2001;69(suppl):504.

    External Resources

  22. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors II: marker-locus genotyping errors modeled with hypercomplex recombination fractions. Am J Hum Genet 2000;66:1107–1118.
  23. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors I: complex-valued recombination fractions and complex phenotypes. Am J Hum Genet 2000;66:1095–1106.
  24. Blackwelder WC, Elston RC: A comparison of sib-pair linkage tests for disease susceptibility loci. Genet Epidemiol 1985;2:85–97.
  25. Nordheim EV, O’Malley DM, Chow SC: On the performance of a likelihood ratio test for genetic linkage. Biometrics 1984;40:785–790.

    External Resources

  26. Penrose LS: The detection of autosomal linkage in data which consist of pairs of brothers and sisters of unspecified parentage. Ann of Eug 1935;133–138.

    External Resources

  27. Göring HH, Terwilliger JD: Linkage analysis in the presence of errors III: marker loci and their map as nuisance parameters. Am J Hum Genet 2000;66:1298–1309.
  28. Falk CT, Rubinstein P: Haplotype relative risks: an easy reliable way to construct a proper control sample for risk calculations. Ann Hum Genet 1987;51:227–233.
  29. Terwilliger JD, Ott J: A haplotype-based ‘haplotype relative risk’ approach to detecting allelic associations. Hum Hered 1992;42:337–346.
  30. Spielman RS, McGinnis RE, Ewens WJ: Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet 1993;52:506–516.
  31. Terwilliger JD: On the resolution and feasibility of genome scanning approaches. Adv Genet 2001;42:351–391.
  32. Cottingham RW Jr, Idury RM, Schäffer AA: Faster sequential genetic linkage computations. Am J Hum Genet 1993;53:252–263.
  33. Lathrop GM, Lalouel JM, Julier C, Ott J: Strategies for multilocus linkage analysis in humans. Proc Natl Acad Sci USA 1984;81:3443–3446.
  34. Lathrop GM, Lalouel JM, White RL: Construction of human linkage maps: likelihood calculations for multilocus linkage analysis. Genet Epidemiol 1986;3:39–52.
  35. Schäffer AA, Gupta SK, Shriram K, Cottingham RW Jr: Avoiding recomputation in linkage analysis. Hum Hered 1994;44:225–237.
  36. Simard LR, Prescott G, Rochette C, Morgan K, Lemieux B, Mathieu J, Melancon SB, Vanasse M: Linkage disequilibrium analysis of childhood-onset spinal muscular atrophy (SMA) in the French-Canadian population. Hum Mol Genet 1994;3:459–463.
  37. Ott J: Estimation of the recombination fraction in human pedigrees: efficient computation of the likelihood for human linkage studies. Am J Hum Genet 1974;26:588–597.
  38. Elston RC, Stewart J: A general model for the genetic analysis of pedigree data. Hum Hered 1971;21:523–542.
  39. Lalouel JM: GEMINI – A Computer Program for Optimization of a Nonlinear Function. Department of Medical Biophysics and Computing, University of Utah, Salt Lake City, 1979.
  40. Torczon V: On the convergence of the multidirectional search algorithm. SIAM J Optim 1991;1:123–145.

    External Resources

  41. Terwilliger JD, Ott J: Handbook of Human Genetic Linkage. Johns Hopkins University Press, Baltimore, 1994.
  42. Mukhopadhyay N, Almasy L, Schroeder M, Mulvihill WP, Weeks DE: Mega2, a data-handling program for facilitating genetic linkage and association analyses. Am J Hum Genet 1999;65:A436.

    External Resources

  43. Becker A, Geiger D, Schäffer AA: Automatic selection of loop breakers for genetic linkage analysis. Hum Hered 1998;48:49–60.
  44. Dennis JE Jr, Torczon V: Direct search methods on parallel machines. SIAM J Optim 1991;1:448–474.

    External Resources

  45. Wessman M, Kallela M, Kaunisto MA, Marttila P, Sobel E, Hartiala J, Oswell G, Leal SM, Papp JC, Hämäläinen E, Broas P, Joslyn G, Hovatta I, Hiekkalinna T, Kaprio J, Ott J, Cantor RM, Zwart JA, Ilmavirta M, Havanka H, Färkkilä M, Peltonen L, Palotie A: A susceptibility locus for migraine with aura, on chromosome 4q24. Am J Hum Genet 2002;70:652–662.
  46. Kaunisto MA, Tikka PJ, Kallela M, Leal SM, Papp JC, Korhonen A, Hämäläinen E, Harno H, Havanka H, Nissilä M, Säkö E, Ilmavirta M, Kaprio J, Färkkilä M, Ophoff RA, Palotie A, Wessman M: Chromosome 19p13 loci in Finnish migraine with aura families. Am J Med Genet B Neuropsychiatr Genet 2005;132:85–89.
  47. Ekelund J, Hovatta I, Parker A, Paunio T, Varilo T, Martin R, Suhonen J, Ellonen P, Chan G, Sinsheimer JS, Sobel E, Juvonen H, Arajärvi R, Partonen T, Suvisaari J, Lönnqvist J, Meyer J, Peltonen L: Chromosome 1 loci in Finnish schizophrenia families. Hum Mol Genet 2001;10:1611–1617.
  48. Hiekkalinna T, Göring HHH, Lambert BW, Weiss KM, Norrgrann P, Schäffer AA, Terwilliger JD: On the statistical properties of family-based association tests in datasets containing both pedigrees and unrelated case-control samples. Under review 2011.
  49. Lambert BW, Terwilliger JD, Weiss KM: ForSim: a tool for exploring the genetic architecture of complex traits with controlled truth. Bioinformatics 2008;24:1821–1822.
  50. Ott J: Computer-simulation methods in human linkage analysis. Proc Natl Acad Sci USA 1989;86:4175–4178.
  51. Weeks DE, Ott J, Lathrop GM: SLINK: a general simulation program for linkage analysis. Am J Hum Genet 1990;A204.
  52. Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES: Parametric and nonparametric linkage analysis: a unified multipoint approach. Am J Hum Genet 1996;58:1347–1363.
  53. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC: PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–575.