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| − | == | + | ==Training Resources in Statistical Genetics== |
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| − | + | We are an international group of statistical geneticists who wish to make training resources available to the genetics community. We offer tutorials for a variety of analysis tools/software. We also offer courses on a variety of topics related to analysis of human genetic data. | |
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| − | == | + | ===Our group=== |
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| − | + | * Heather Cordell, Ph.D. (Newcastle University) | |
| − | + | * Andrew DeWan, Ph.D. (Yale University) | |
| − | * | + | * Suzanne M. Leal, Ph.D. (Columbia University and Rockefeller University) |
| − | * | + | * Michael Nothnagel, Ph.D. (University of Cologne) |
| − | * | + | * Gao T. Wang, Ph.D. (Columbia University) |
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| − | + | Material on this site are open source and can be found on GitHub at https://github.com/statgenetics/statgen-courses | |
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| + | For questions concerning material on this site please raise them at the Discussion forum curated by our team, https://github.com/statgenetics/statgen-courses/discussions | ||
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==Statistical Genetics Courses== | ==Statistical Genetics Courses== | ||
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* [[Tutorials#SLINK|SLINK]] | [https://github.com/statgenetics/statgen-courses/blob/master/docker/slink.dockerfile dockerfile] and [https://hub.docker.com/r/statisticalgenetics/slink/tags docker image] | * [[Tutorials#SLINK|SLINK]] | [https://github.com/statgenetics/statgen-courses/blob/master/docker/slink.dockerfile dockerfile] and [https://hub.docker.com/r/statisticalgenetics/slink/tags docker image] | ||
* [[Tutorials#Variant_Association_Tools|Variant Association Tools]] | [https://github.com/statgenetics/statgen-courses/blob/master/docker/vat.dockerfile dockerfile] and [https://hub.docker.com/r/statisticalgenetics/vat/tags docker image] | * [[Tutorials#Variant_Association_Tools|Variant Association Tools]] | [https://github.com/statgenetics/statgen-courses/blob/master/docker/vat.dockerfile dockerfile] and [https://hub.docker.com/r/statisticalgenetics/vat/tags docker image] | ||
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Revision as of 16:18, 1 February 2022
Training Resources in Statistical Genetics
We are an international group of statistical geneticists who wish to make training resources available to the genetics community. We offer tutorials for a variety of analysis tools/software. We also offer courses on a variety of topics related to analysis of human genetic data.
Our group
- Heather Cordell, Ph.D. (Newcastle University)
- Andrew DeWan, Ph.D. (Yale University)
- Suzanne M. Leal, Ph.D. (Columbia University and Rockefeller University)
- Michael Nothnagel, Ph.D. (University of Cologne)
- Gao T. Wang, Ph.D. (Columbia University)
Material on this site are open source and can be found on GitHub at https://github.com/statgenetics/statgen-courses
For questions concerning material on this site please raise them at the Discussion forum curated by our team, https://github.com/statgenetics/statgen-courses/discussions
Statistical Genetics Courses
Genetic Association
September 26-30, 2022
Max Delbrück Center for Molecular Medicine, Berlin, Germany
Advanced Gene Mapping
November 7-11, 2022
The Rockefeller University, New York, USA
Previous Course Pages
Tutorials for Courses
- ANNOVAR Annotation | dockefile and docker image
- Cochran Armitage Trend Test for GWAS power analysis
- Family-based Association using FaST-LMM, PLINK and R | dockefile and docker image
- IGV | dockerfile and docker image
- Gemini | dockerfile and docker image
- GCTA | dockefile and docker image
- GWAS: QC | dockerfile and docker image
- GWAS: Controlling for Population Substructure | dockerfile and docker image
- Interaction analysis using PLINK and CASSI | dockerfile and docker image
- LINKAGE | dockerfile and docker image
- Population Genetics | dockefile and docker image
- Pleiotropy | dockefile and docker image
- Polygenic risk prediction using non-parametric shrinkage | dockefile and docker image
- PLINK/SEQ (PSEQ) | dockefile and docker image
- Regression | dockefile and docker image
- RV-TDT
- SEQLinkage
- SEQSpark
- SLINK | dockerfile and docker image
- Variant Association Tools | dockerfile and docker image
