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PubH 8400 Advanced Statistical Genetics and Genomics - Spring 2007
PubH 8400 Advanced Statistical Genetics and Genomics - Spring 2008
- Meeting Time & Place: PWB 6-210, T & Th 11:15AM - 12:30PM
- Meeting Time & Place: Moos T 2-116, T & Th 11:15AM - 12:30PM
- Homework 2 - Due on Mar 8.
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- Some References Books in Statistical Genetics (summary taken from Amazon.com, comments are mine)
- Some textbooks in Statistical Genetics (summary taken from Amazon.com, comments are mine)
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- Some References Books in Statistical Genetics
- Some References Books in Statistical Genetics (summary taken from Amazon.com, comments are mine)
- Homework 1 - Due on Feb 6.
- Homework 1 - Due on Feb 6.
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library) - Some References Books in Statistical Genetics
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library)
- Some References Books in Statistical Genetics
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library) - Some References Books in Statistical Genetics
(The summary is from Amazon.com and the comments are mine, if there are any.)
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library) - Some References Books in Statistical Genetics
- Some References Books in Statistical Genetics (The summary is from Amazon.com and the comments are mine, if there are any.)
- Some References Books in Statistical Genetics
(The summary is from Amazon.com and the comments are mine, if there are any.)
- Some References Books in Statistical Genetics
- Some References Books in Statistical Genetics (The summary is from Amazon.com and the comments are mine, if there are any.)
- Some References Books in Statistical Genetics
- Homework 1
- Homework 1 - Due on Feb 6.
- Homework 1
- Meeting Time & Place: T & Th 11:15AM - 12:30PM
- Office Hours: TBA
- Meeting Time & Place: PWB 6-210, T & Th 11:15AM - 12:30PM
- Office Hours: By appointment
- Additional Part I (Statistical Genetics) Information
There will be about 6 homeworks and a final project, contributing 60% and 40% to the final grade respectively.
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library)
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library)
- Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics (Access through UMN Library)
- You can keep up with changes of the course website by subscribing to the
- You can keep up with changes of the course website by subscribing to the RSS feed (What is RSS?)
- You can keep up with changes of the course website by subscribing to the
Resources
Resources
Suggested Reading Material
Web Links
1. Introduction; meiosis indicator, identity by descent and identity coefficients, likelihood.
2. Linkage analysis, LOD score, Elston-Stewart and Lander-Green algorithms, MCMC methods, nonparametric linkage.
3. Quantitative traits, variance component linkage methods.
4. Modern population genetics, coalescent theory and its applications (2 weeks).
5. Population based association studies, linkage disequilibrium, haplotype, population admixture. (2 weeks) 6. Family based association, TDT methods, design of family based studies. 7. Introduction to array technology: microarray, SNP array, mass spectrometry. 8. Low-level analysis: pre-processing of cDNA/Affy/SNP arrays (1.5 weeks). 9. High-level analysis I: differential gene expression detection and multiple comparison. 10. High-level analysis II: prediction, clustering, interaction modeling(2 weeks). 11. Analysis of mass spectrometry data.
- Introduction; meiosis indicator, identity by descent and identity coefficients, likelihood.
- Linkage analysis, LOD score, Elston-Stewart and Lander-Green algorithms, MCMC methods, nonparametric linkage.
- Quantitative traits, variance component linkage methods.
- Modern population genetics, coalescent theory and its applications (2 weeks).
- Population based association studies, linkage disequilibrium, haplotype, population admixture. (2 weeks)
- Family based association, TDT methods, design of family based studies.
- Introduction to array technology: microarray, SNP array, mass spectrometry.
- Low-level analysis: pre-processing of cDNA/Affy/SNP arrays (1.5 weeks).
- High-level analysis I: differential gene expression detection and multiple comparison.
- High-level analysis II: prediction, clustering, interaction modeling(2 weeks).
- Analysis of mass spectrometry data.
1. Introduction; meiosis indicator, identity by descent and identity
coefficients, likelihood.
2. Linkage analysis, LOD score, Elston-Stewart and Lander-Green
algorithms, MCMC methods, nonparametric linkage.
1. Introduction; meiosis indicator, identity by descent and identity coefficients, likelihood. 2. Linkage analysis, LOD score, Elston-Stewart and Lander-Green algorithms, MCMC methods, nonparametric linkage.
4. Modern population genetics, coalescent theory and its applications (2
weeks).
5. Population based association studies, linkage disequilibrium,
haplotype, population admixture. (2 weeks)
4. Modern population genetics, coalescent theory and its applications (2 weeks). 5. Population based association studies, linkage disequilibrium, haplotype, population admixture. (2 weeks)
7. Introduction to array technology: microarray, SNP array, mass
spectrometry.
8. Low-level analysis: pre-processing of cDNA/Affy/SNP arrays (1.5
weeks).
9. High-level analysis I: differential gene expression detection and
multiple comparison.
10. High-level analysis II: prediction, clustering, interaction modeling
(2 weeks).
7. Introduction to array technology: microarray, SNP array, mass spectrometry. 8. Low-level analysis: pre-processing of cDNA/Affy/SNP arrays (1.5 weeks). 9. High-level analysis I: differential gene expression detection and multiple comparison. 10. High-level analysis II: prediction, clustering, interaction modeling(2 weeks).
Notes
Course Outline and Notes
1. Introduction; meiosis indicator, identity by descent and identity
coefficients, likelihood.
2. Linkage analysis, LOD score, Elston-Stewart and Lander-Green
algorithms, MCMC methods, nonparametric linkage.
3. Quantitative traits, variance component linkage methods. 4. Modern population genetics, coalescent theory and its applications (2
weeks).
5. Population based association studies, linkage disequilibrium,
haplotype, population admixture. (2 weeks)
6. Family based association, TDT methods, design of family based studies. 7. Introduction to array technology: microarray, SNP array, mass
spectrometry.
8. Low-level analysis: pre-processing of cDNA/Affy/SNP arrays (1.5
weeks).
9. High-level analysis I: differential gene expression detection and
multiple comparison.
10. High-level analysis II: prediction, clustering, interaction modeling
(2 weeks).
11. Analysis of mass spectrometry data.
- Meeting Time & Place: TBD
- Meeting Time & Place: T & Th 11:15AM - 12:30PM
title Statistical Genetics and Genomics II
PubH 8400 Statistical Genetics and Genomics II - Spring 2007
(:title Advanced Statistical Genetics and Genomics:)
PubH 8400 Advanced Statistical Genetics and Genomics - Spring 2007
- [(Attach:)Syllabus.pdf]
- [(Attach:)Syllabus.pdf]
- [Attach:statgen2-syllabus.pdf | Syllabus]
- Meeting Time & Place: TBD
- Office Hours: TBA
- [Attach:statgen2-syllabus.pdf | Syllabus]
* Instructors: Na Li (nali@umn.edu) and Baolin Wu (baolin@umn.edu)
- Instructors: Na Li (nali@umn.edu) and Baolin Wu (baolin@umn.edu)
- Instructors: Na Li (nali@umn.edu) and Baolin Wu (baolin@umn.edu)
* Instructors: Na Li (nali@umn.edu) and Baolin Wu (baolin@umn.edu)
- Instructors: Na Li (nali@umn.edu) and Baolin Wu (baolin@umn.edu)
PubH 8400 Statistical Genetics and Genomics II - Spring 2007
PubH 8400 Statistical Genetics and Genomics II - Spring 2007
Information
Notes
Homework and Projects
Resources
title Statistical Genetics and Genomics II
(:title Statistical Genetics and Genomics II:)
PubH 8400 Statistical Genetics and Genomics II - Spring 2007
(:title Statistical Genetics and Genomics II:)


