Information Package / Course Catalogue
Statistical Genetics
Course Code: BİS536
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 6
Objectives of the Course

This course provides an introduction to the models and methods of Statistical Genetics for students with little Genetics background but with some knowledge of Probability and Statistics. The course provides a basis for further study in Statistical Genetics.

Course Content

Mendelian genetic traits. Hardy-Weinberg, allelic variation, subdivision. Likelihood inference, latent variables and EM algorithm. Pedigree relationships and gene identity. Meiosis and recombination. Linkage detection. Multipoint linkage analysis.

Name of Lecturer(s)
Learning Outcomes
1.Be able to statistically relate genetic and environmental effects to a quantative trait
2.Be able to identify procedures for estimation of genetic and enviromental effects
3.Be able to identify methods for localization of genes that influence variation in quantitative traits
4.Be able to identify methods for quantifying the affects of genetic variants on quantitative traits
5.Be able to read/understand the current applied and theoretical literature involving genetic influences on quantitative traits
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Overview of genome mapping
Week 2 - Theoretical
Basic genetics: Mendelian genetics,Population & quantitative genetics,Marker segregation analysis
Week 3 - Theoretical
Simple Mendelian traits; Mendelian segregation, dominant and recessive traits, X-linked traits, patterns of inheritance.
Week 4 - Theoretical
Population genetic issues; testing Hardy-Weinberg equilibrium, likelihood estimation of allele frequencies, the EM algorithm
Week 5 - Theoretical
Haplotypes, allelic association and haplotyping. Likelihood estimation of haplotype frequencies. Mutation, selection, and random genetic drift.
Week 6 - Theoretical
Kinship and gene identity by descent; probabilities on pedigrees.
Week 7 - Theoretical
Genetic linkage; meiosis and recombination, twolocus kinship and gene identity, linkage disequilibrium, Two-locus linkage analysis, the probabilities of meiosis patterns-1
Week 8 - Intermediate Exam
Midterm exam
Week 9 - Theoretical
Genetic linkage; meiosis and recombination, twolocus kinship and gene identity, linkage disequilibrium, Two-locus linkage analysis, the probabilities of meiosis patterns-2
Week 10 - Theoretical
Simple designs for two-locus linkage; testing for linkage, expected lod scores and power to detect linkage, homozygosity mapping-1
Week 11 - Theoretical
Simple designs for two-locus linkage; testing for linkage, expected lod scores and power to detect linkage, homozygosity mapping-2
Week 12 - Theoretical
Meiosis, recombination and map functions.
Week 13 - Theoretical
Multipoint linkage analysis; the hidden Markov model for multipoint linkage.
Week 14 - Theoretical
The Baum algorithms; the EM algorithm for map estimation.
Week 15 - Theoretical
Literature review and discussion.
Week 16 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Assignment110010
Individual Work140228
Quiz142142
Midterm Examination120222
Final Examination120222
TOTAL WORKLOAD (hours)152
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
5
5
5
5
5
5
4
5
5
5
OÇ-2
5
5
4
5
5
5
5
5
5
4
OÇ-3
4
5
5
5
4
4
4
4
4
3
OÇ-4
5
3
4
5
4
5
4
5
3
4
OÇ-5
5
4
5
4
5
4
5
4
5
4
Adnan Menderes University - Information Package / Course Catalogue