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===== ''Single Cell Sequencing'' ===== | ===== ''Single Cell Sequencing'' ===== | ||
| − | * [https://www.ncbi.nlm.nih.gov/pubmed/26000488 Macosko et al (2015) Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. ''Cell'] <br /> Landmark paper for DropSeq method | + | * [https://www.ncbi.nlm.nih.gov/pubmed/26000488 Macosko E et al (2015) Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. ''Cell'] <br /> Landmark paper for DropSeq method |
| − | * [https://www.ncbi.nlm.nih.gov/pubmed/28091601 (2017) Massively parallel digital transcriptional profiling of single cells. ''Nat Comm''] <br /> Paper from 10x genomics | + | * [https://www.ncbi.nlm.nih.gov/pubmed/28091601 Zheng G et al (2017) Massively parallel digital transcriptional profiling of single cells. ''Nat Comm''] <br /> Paper from 10x genomics |
* [https://lvdmaaten.github.io/publications/papers/JMLR_2008.pdf van der Maaten LJP and Hinton GE (2008) Visualizing Data using t-SNE ''J Machine Learning Research''] <br /> First paper of t-SNE method | * [https://lvdmaaten.github.io/publications/papers/JMLR_2008.pdf van der Maaten LJP and Hinton GE (2008) Visualizing Data using t-SNE ''J Machine Learning Research''] <br /> First paper of t-SNE method | ||
Revision as of 16:13, 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
- Macosko E et al (2015) Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell'
Landmark paper for DropSeq method - Zheng G et al (2017) Massively parallel digital transcriptional profiling of single cells. Nat Comm
Paper from 10x genomics - van der Maaten LJP and Hinton GE (2008) Visualizing Data using t-SNE J Machine Learning Research
First paper of t-SNE method
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
