Difference between revisions of "Main Page"
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==== Papers ====  | ==== Papers ====  | ||
| − | ==== ''Methods for genome-wide association studies (GWAS)'' ====  | + | ===== ''Methods for genome-wide association studies (GWAS)'' =====  | 
* [https://www.ncbi.nlm.nih.gov/pubmed/16415888 Skol AD et al. (2006) "Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies" ''Nat. Genet''] <br /> - Useful to understand basic methods for GWAS and study design  | * [https://www.ncbi.nlm.nih.gov/pubmed/16415888 Skol AD et al. (2006) "Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies" ''Nat. Genet''] <br /> - Useful to understand basic methods for GWAS and study design  | ||
* [https://www.ncbi.nlm.nih.gov/pubmed/20616382 Willer CJ et al. (2010) "METAL: fast and efficient meta-analysis of genomewide association scans." ''Nat Genet''] <br /> - Software tool for meta-analysis  | * [https://www.ncbi.nlm.nih.gov/pubmed/20616382 Willer CJ et al. (2010) "METAL: fast and efficient meta-analysis of genomewide association scans." ''Nat Genet''] <br /> - Software tool for meta-analysis  | ||
| − | ==== ''DNA sequencing and De-novo assembly'' ====  | + | ===== ''DNA sequencing and De-novo assembly'' =====  | 
* [https://www.ncbi.nlm.nih.gov/pubmed/20981092 The 1000 Genomes Project Consortium (2010) A map of human genome variation from population-scale sequencing ''Nature''] <br /> First 1000 genomes paper  | * [https://www.ncbi.nlm.nih.gov/pubmed/20981092 The 1000 Genomes Project Consortium (2010) A map of human genome variation from population-scale sequencing ''Nature''] <br /> First 1000 genomes paper  | ||
* [https://www.ncbi.nlm.nih.gov/pubmed/26432245 The 1000 Genomes Project Consortium (2015) A global reference for human genetic variation ''Nature''] <br /> Final release of the 1000 Genomes Project  | * [https://www.ncbi.nlm.nih.gov/pubmed/26432245 The 1000 Genomes Project Consortium (2015) A global reference for human genetic variation ''Nature''] <br /> Final release of the 1000 Genomes Project  | ||
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* [https://www.ncbi.nlm.nih.gov/pubmed/19451168 |Li et al (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ] <br /> Sequence alignment algorithm using BWT  | * [https://www.ncbi.nlm.nih.gov/pubmed/19451168 |Li et al (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ] <br /> Sequence alignment algorithm using BWT  | ||
| − | ==== ''Single Cell Sequencing'' ====  | + | ===== ''Single Cell Sequencing'' =====  | 
| − | ==== ''Prediction of Gene Expression and/or Complex Phenotypes'' ====  | + | ===== ''Prediction of Gene Expression and/or Complex Phenotypes'' =====  | 
Revision as of 15:05, 11 June 2017
Welcome to the U-M Big Data Summer Institute 2017 Wiki!
Consult the User's Guide for information on using the wiki software.
Contents
- 1 Reading Material
 - 2 2017 Presentations
 - 3 Symposium
 - 4 Additional Resources
 
Reading Material
Data Mining / Machine Learning Group
EHR Group
Genomics Group
Papers
Methods for genome-wide association studies (GWAS)
-  Skol AD et al. (2006) "Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies" Nat. Genet 
- Useful to understand basic methods for GWAS and study design -  Willer CJ et al. (2010) "METAL: fast and efficient meta-analysis of genomewide association scans." Nat Genet 
- Software tool for meta-analysis 
DNA sequencing and De-novo assembly
-  The 1000 Genomes Project Consortium (2010) A map of human genome variation from population-scale sequencing Nature 
First 1000 genomes paper -  The 1000 Genomes Project Consortium (2015) A global reference for human genetic variation Nature 
Final release of the 1000 Genomes Project -  Iqbal Z. et al (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. Nature 
Variant caller using de-novo assembly graphs -  |Li et al (2009) Fast and accurate short read alignment with Burrows-Wheeler transform.  
Sequence alignment algorithm using BWT 
Single Cell Sequencing
Prediction of Gene Expression and/or Complex Phenotypes
Online videos to better understand genetics and genomics
Genetics
- Introduction to Genetics by 23andMe (5 videos)
 - TED-Ed : How Mendel's pea plants helped us understand genetics - Hortensia Jiménez Díaz
 - Genetic Recombination and Gene Mapping by Bozeman Science
 - Useful Genetics : A college-level comprehensive genetics course with 292 lectures offered by Rosie Redfield at UBC
 
Useful 3D Animations
- From DNA to protein - 3D Animation
 - DNA Transcription - 3D Animation
 - DNA splicing - 3D Animation
 - mRNA Translation - 3D Animation
 - How DNA is packaged - 3D Animation
 - The Central Dogma - 3D Animation
 
Gene Regulation and Epigenetics
- Epigenetics Lecture by SciShow
 - Hi-C Technique : A 3D map of the Human Genome
 - The ENCODE Project
 - RNAi by Nature Video
 
Sequencing Technologies
- TED-Ed : The race to sequence the human genome - Tien Nguyen
 - DropSeq - Droplet-based Single Cell Sequencing by McCarroll Lab
 
Imaging Group
2017 Presentations
Week 1
Day 1: June 6
- Orientation 2017 (Slides) - Bhramar Mukherjee, PhD
 - Coordinator Presentation (Slides) - Mitch Sevingy
 - Life in Ann Arbor (Slides) - Mitch Sevigny
 - On Being a Scientist (Slides & Audio) - Bhramar Mukherjee, PhD
 - Ethics Review (Slides) - Bhramar Mukherjee, PhD
 - Basic Probability (Audio) - Robert Klemmer
 
Day 2: June 7
- Data Processing (Slides & Audio) - Jed Carlson
 - Study Design and Inference (Slides & Audio) - Rod Little, PhD
 - Basic Unix (Slides) - Hyun Min Kang, PhD
 
Day 3: June 8
- R 101 (Notes & Audio) - Matthew Flickinger, PhD
 - Observational Data and Bias (Slides & Audio) - Rod Little, PhD
 - Linear Algebra (Audio) - Robert Klemmer
 
Day 4: June 9
- R 102 (Notes & Audio) - Matthew Flickinger, PhD
 - Matrix Computation (Slides & Audio) - Shawn Lee, PhD
 - Sebastian Zoellner Journey (Slides & Audio) - Sebastian Zoellner, PhD
 - R 103 - Matthew Flickinger, PhD
 
Week 2
Day 5: June 12
Day 6: June 13
Day 7: June 14
Day 8: June 15
Day 9: June 16
Week 3
Day 10: June 19
Day 11: June 20
Day 12: June 21
Day 13: June 22
Day 14: June 23
Week 4
Day 15: June 26
Day 16: June 27
Day 17: June 28
Day 18: June 29
Day 19: June 30
Week 5
Day 20: July 3
Day 22: July 5
Day 23: July 6
Day 24: July 7
Week 6
Day 25: July 10
Day 26: July 11
Day 27: July 12
Symposium
Student Group Presentations
Student Poster Presentations