HSPH Mini-Course on Computational Tools and Statistical Methods for SNPs (Syllabus, reading list).
Course Organizers: Tianhua Niu and Peter Kraft
Friday, May 5, 2006, 1:30PM-3:00PM
Lecture 1. Contemporary Computational Tools and SNP Databases
SPEAKER: Isaac Kohane (Children's Hospital) (slide, Lecture video)
3:15PM-4:45PM
Lecture 2. Issues in Large-Scale SNP-based Experimental Designs
SPEAKER: Tim Niu (BWH/HSPH) (handout, lecture video)
Friday, May 12, 2006, 1:30PM-3:00PM
Lecture 3. "SNP Browser" program (ABI)
SPEAKER: Chris Read (ABI) (hard copy of handout available upon request, lecture video)
Friday, May 19, 2006, 1:30PM-3:00PM
Lecture 4. Tagging SNP Selection Methods for Genetic Studies
SPEAKER: Mark Daly (MGH/Broad Institute) (handout)
3:15PM-4:45PM
Lecture 5. Efficiency and Power Comparisons for SNP-based vs.
Haplotype-based Analytic Strategies
SPEAKER: Paul de Bakker (MGH/Broad Institute) (handout)
Friday, May 26, 2006, 1:30PM-3:00PM [** Location: Kresge LL-6]
Lecture 6. Whole-Genome Admixture Scan
SPEAKER: David Reich (HMS) (lecture video, handout, ref1, ref2, ref3)
3:15PM-4:45PM
Lecture 7. Analysis of Copy Number Analysis and Loss-Of-Heterozygosity
Using Affymetrix SNP Arrays
SPEAKER: Cheng Li (DFCI) (handout, sample data, lecture video)
Friday, June 2, 2006, 1:30PM-3:00PM
Lecture 8. Whole Genome Association Studies in Case-Control Setting
SPEAKER: Peter Kraft (HSPH) (handout, Lecture video)
3:15PM-4:45PM
Lecture 9. Whole Genome Association Studies in Family-based Setting
SPEAKER: Christoph Lange (Channing/HSPH) (handout, Lecture video)
Registration is required and seats are limited.
Please RSVP to xinlu@hsph.harvard.edu
Tutorial on GenePattern system. March 28, 8:30am - 5:00pm, Kresge LL-6.
GenePattern is a flexible analysis platform developed to support multidisciplinary biomedical research. GenePattern puts the power of sophisticated computational methods into the hands of non-programming users. It also provides an environment for rapid development and deployment of new analytic techniques.
Speaker: Professor Michael Reich, Broad Institute
Registration is required and seats are limited.
Please RSVP to xinlu@hsph.harvard.edu
Mini-Course on Machine Learning Methods in High-Throughput Biological Data Analysis (Syllabus)
Friday, February 10, 1:30-3:30pm, Kresge G3: Overview of Machine Learning and Pattern Recognition Methods and their applications, include: Hierarchical Clustering, Fisher's LDA, Nearest Neighbor, K-means clustering, Artificial Neural Network and SOM. (lecture notes 1, 2, lecture video 1, 2)
Friday, February 17, 1:30-3:30pm, Kresge G3: Detailed discussion on unsupervised and supervised learning, and feature selection, include: Support Vector Machine and Statistical Learning Theory, assessment of performance and choice of methods. (lecture notes 3, 4, lecture video 3/4)
Friday, February 24, 1:30-3:30pm, Kresge LL-6: Computer lab session on Hand-on lab training on R and machine learning algorithms, include: basic introduction of R environment and bioconductor packages, and the usage of Hierarchical Clustering, SOM, LDA, KNN, SVM, and R-SVM for microarray data analysis. (LabNote, SampleData)
Instructor:
Dr. Xuegong Zhang. Professor of Pattern Recognition and Bioinformatics, Tsinghua University. zhangxg@tsinghua.edu.cn
Registration is required and seats are limited.
Please RSVP to xinlu@hsph.harvard.edu