Course Website Locator: epi293-01

Harvard School of Public Health

The following course websites match your request:

Winter 2010

Dr. P. Kraft
2.50 credits
Lectures, case studies. Eight 3-hour sessions and three computer labs during WinterSession.

This course introduces the conceptual and practical tools needed for genetic association studies using unrelated subjects. Students will gain hands-on experience with a range of analytic tools and software packages as part of a class project which gives them the opportunity to design and analyze an association study. This project will require students to tackle real-world problems such as marker selection, potential multiple comparisons issues due to multiple markers and multiple outcomes, and missing data. Lectures and selected readings present key ideas (such as linkage disequilibrium, "tagging SNPs," haplotypes, population stratification and epistasis) and appropriate statistical methods.
Course note: BIO201, EPI201 and at least one of BIO210, BIO213 or EPI204, or signature of instructor required. Familiarity with SAS or S-PLUS/R and UNIX computing environment also highly recommended. (5.06)

Winter 2009

Dr. P. Kraft
2.50 credits
Lectures, case studies. Eight 3-hour sessions and three computer labs during WinterSession.

This course introduces the conceptual and practical tools needed for genetic association studies using unrelated subjects. Students will gain hands-on experience with a range of analytic tools and software packages as part of a class project which gives them the opportunity to design and analyze an association study. This project will require students to tackle real-world problems such as marker selection, potential multiple comparisons issues due to multiple markers and multiple outcomes, and missing data. Lectures and selected readings present key ideas (such as linkage disequilibrium, "tagging SNPs," haplotypes, population stratification and epistasis) and appropriate statistical methods.
Course note: BIO201, EPI201 and at least one of BIO210, BIO213 or EPI204, or signature of instructor required. Familiarity with SAS or S-PLUS/R and UNIX computing environment also highly recommended. (5.06)

Winter 2008

Dr. P. Kraft
2.50 credits
Lectures, case studies. Eight 3-hour sessions and three computer labs during WinterSession.

This course introduces the conceptual and practical tools needed for genetic association studies using unrelated subjects. Students will gain hands-on experience with a range of analytic tools and software packages as part of a class project which gives them the opportunity to design and analyze an association study. This project will require students to tackle real-world problems such as marker selection, potential multiple comparisons issues due to multiple markers and multiple outcomes, and missing data. Lectures and selected readings present key ideas (such as linkage disequilibrium, "tagging SNPs," haplotypes, population stratification and epistasis) and appropriate statistical methods.
Course note: BIO201, EPI201 and at least one of BIO210, BIO213 or EPI204, or signature of instructor required. Familiarity with SAS or S-PLUS/R and UNIX computing environment also highly recommended. (5.06)

Winter 2007

Dr. P. Kraft
2.50 credits
Lectures, case studies. Eight 3-hour sessions and three computer labs during WinterSession.

This course introduces the conceptual and practical tools needed for genetic association studies using unrelated subjects. Students will gain hands-on experience with a range of analytic tools and software packages as part of a class project which gives them the opportunity to design and analyze an association study. This project will require students to tackle real-world problems such as marker selection, potential multiple comparisons issues due to multiple markers and multiple outcomes, and missing data. Lectures and selected readings present key ideas (such as linkage disequilibrium, "tagging SNPs," haplotypes, population stratification and epistasis) and appropriate statistical methods.
Course note: BIO201, EPI201 and at least one of BIO210, BIO213 or EPI204, or signature of instructor required. Familiarity with SAS or S-PLUS/R and UNIX computing environment also highly recommended. (5.06)

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