Statistical Genetics

CHL 5224 Fall 2008
http://fisher.utstat.toronto.edu/sun/chl5224_index.html

 

General Information

  • Time: Tuesdays 10:00 - 1pm (classes will start at 10am sharp. Please arrive on time).
  • Location: HSB 790.
    HSB: Health Sciences Building, 155 College Street (South on College and West of University).

Instructors

  • Lei Sun (sun@utstat.toronto.edu)
  • Wei Xu (wxu@uhnres.utoronto.ca)

Office Hour

  • Tuesdays noon/12:30pm-1pm (the last hour or half hour of the class).

Prerequisites and Enrollment

  • This is a graduate course with the following prerequisites.
    • Statistics at the graduate level or consent of instructor.
    • Working knowledge of UNIX platform is necessary. There will be one or more simulation studies (no tutorial) and use of GENEHUNTER and PLINK software packages (with tutorial).


  • Graduate students (both Master and PhD levels) in the biostatistics and statistics programs are strongly encouraged to participate.


  • All participating graduate students must register! This is a graduate school policy. Postdocs and research fellows are welcome to sit-in.

  • Computational programs and softwares: R/SPLUS (or C/C++), SAS, GENEHUNTER, PLINK, FBAT.

    • October 1, 2008: the final date to enroll the course.
    • October 29, 2008: the final date to withdraw from the course.

Course Information

  • Teaching objectives

    This course is for students of biostatistics, epidemiology and statistics with little genetics background but with some knowledge of probability and statistics. This course covers the fundamental statistical problems in genetics, with an emphasis on human genetics. The aim of the course is to provide students necessary background and prepare them for advanced study and research in the area of statistical genetics. This course is a prerequisite for course Computational Methods for Statistical Genetics offered in Winter 2009.
  • Format of instruction

    The course will have the regular formats - e.g. lectures and computing labs.
  • Evaluation

    Student evaluation will be based on four homework problem sets (60%), two lab projects (30%) and overall participation in classes (10%).
  • Recommended books
    • For basic genetics background
      • Gonick L, Wheelis M (1991). Cartoon guide to genetics. Revised edition. HarperCollins.
      • Virtually any genetics textbook.
    • For statistical genetics
      • Sham P (1998). Statistics in Human Genetics. Arnold, London.
      • Zieglier A, Koenig I (2006). A Statistical Approach to Genetic Epidemiology: Concepts and Applications. Wiley-VCH, .
      • Thomas DC (2004). Statistical Methods in Genetic Epidemiology. Oxford University Press.
      • Lange K (2002). Mathematical and Statistical Methods for Genetic Analysis. 2nd edition. Springer-Verlag, New York.
      • Ott J (1999). Analysis of Human Genetic Linkage. 3rd edition. Johns Hopkins University Press, Baltimore.

 

Course Outline

  • September 16 - Session 1 ( W Xu)

    Topic: administrative work; introduction and overview. (Notes in PDF file)
    Reading:
    • Elston RC (2000). Introduction and overview. Statistical Methods in Medical Research 9(6):527-541.

Homework: hw1 in PDF file (due in two weeks).

  • September 23 - Session 2 (L Sun)

    Topic: basic genetic terms and principles of population genetics. (Notes in PDF file)
    Reading:
    • Sham's book, chapter 1.

Homework: hw2 in PDF file (due in three weeks).

  • September 30 - Session 3 (W Xu )

    Topic: familial aggregation, single locus inheritance, and segregation analysis. (Notes in PDF file)
    Reading:
    • Liang KY, Beaty TH (2000) Statistical designs for familial aggregation. Statistical Methods in Medical Research 9(6):543-562.
    • Sham's book, chapter 2.

Homework: hw 1 due, hw3 in PDF file (due in three weeks).

  • October 7 - Session 4 (L Sun)

    Topic: multiple locus inheritance, map, and linkage. (Notes in PDF file)
    Reading:
    • McPeek (1996). Introduction to recombination and linkage analysis. IMA Volumes in Mathematics and its Applications, Volume 81, Genetic mapping and DNA sequencing, T. P. Speed and M. S. Waterman, eds., Springer-Verlag New York Publishers.
    • Ott's book Chapter 1.
    • Handbook of Statistical Genetics, Chapter 1 - T. Speed and H. Zhao. Chromosome Maps

Homework: hw2 due

  • October 21 - Session 6 (W Xu)

    Topic: linkage mapping II (Linkage on complex diseases: QTL analysis, G × G (epistasis), and G × E). (Notes in PDF file)
    Reading:
    • Haseman and Elston (1972). The investigation of linkage between a quantitative trait and a marker locus. Behav Genet. Mar;2(1):3–19.
    • Culverhouse et al. (2002).  A perspective on epistasis: limits of models displaying no main effect. Am J Hum Genet.70(2):461-71.
    • Hahn et al. (2003). Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics. 12;19(3):376-82.
    • Xu et al. (2006). A tree-based model for allele-sharing-based linkage analysis in human complex diseases. Genet Epidemiol.30(2):155-69.  

Homework: hw3 due


  • November 4 - Session 8 (W Xu)

    Topic: Association analysis I (LD, case-control study and TDT). (Notes in PDF file)
    Reading:
    • Sham's book, chapter 4.
    • Risch and Merikangas (1996). The future of genetic studies of complex human diseases. Science 273: 1516-1517.
    • Terwilliger and Weiss. (1998). Linkage disequilibrium mapping of complex disease: Fantasy or reality? Curr. Opin. Biotechnol. 9: 578-594.
    • Lewis. (2002) Genetic association studies: Design, analysis and interpretation. Briefings in Bioinformatics 3(2):146-153.

Homework: hw4 in PDF file (due in two weeks).

  • November 11 - Session 9 (W Xu)

    Topic: Association analysis II (Genome wide association study, haplotype analysis). (Notes in PDF file)
    Reading:
    • Devlin B et al. (2001). Genomic control, a newapproach to genetic-based association studies. Theor PopulBiol 60:155.
    • Hirschhorn and Daly. (2005). Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 6(2):95-108.
    • Zaykin D et al.(2002). Testing association of statistical inferred haplotypes with discrete and continuous traits in samples of unrelated individuals.  
    • Fallin D et al. (2001). Genetic analysis of case/control data using estimated haplotype frequencies: application to APOE locus variation and Alzheimer's disease. Genome Res. 11(1):143-51.
    • Montana. (2006). Statistical methods in genetics. Brief Bioinform. 7(3): 297 - 308.  



 

  • November 25 - Session 11 (L Sun)

    Topic: Multiple testing and adjustment. (Notes in PDF file)
    Homework: hw 4 due