Duke NGS Course (Summer 2015)¶
- Assigned Reading
- Lecture notes
- How to Claim and Access Your Virtual Machine
- Installing R, RStudio and IPython notebook with the R kernel
- Installing Graphics Packages
- Basic R in the Jupyter Notebook and RStudio
- Introduction to R
- Preparing Data for Analysis
- Working with Data
- Grouping and Aggregation
- Hypothesis Testing and Power Calculations
- Probability distributions and Random Number Genereation
- Writing Custom Functions
- Functional Programming
- Linear Regression
- Using R for supervised learning
- Supervised Learning Continued - What Could Go Wrong?
- Unsupervised Learning
- Unsupervised Learning and NGS
- Multiple Testing
- Counting Models/Discrete Distributions
- Generalized Linear Models
- Base Graphics
- Plotting Graphcs and Heatmpas
- Introdcution to
ggplot2 - More
ggplot2 - Practice ONE
- Practice TWO
- Practice THREE
- Practice FOUR
- Introduction to DESeq2
- Import count data using basic tools