These are all the computer labs I wrote for a class I TA’d entitled, Quantiative Genetics and Genomics at Cornell University and Weill Cornell Medicine. The base of the computer labs were written by Zoe Zhao, you can get see these labs at her github. There are also video lectures that well correspond to the fundamental mathematics and biology of each lab. You can find these videos at Mezey Lab.
There may still be some bugs within the labs, but for the most part they are great. From basic R to MCMC, these labs provide a way to learn R in the context of genetics. The labs are all based in R-Markdown, which is something I have not seen in many other R lessons so hopefully you can take advantage of that fact here. All of these labs are on my github. The contents of the labs are as follows:
R as a calculator, Matrices and data frames
R Markdown, Functions, For Loops, If Statements, Vector and Matrix calculations
Plotting, Probability Distributions
Boolean Data, Fancy vector indexing, Dealing with missing data
Pseudo-random numbers, Pasting, Speeding up your code
Reading in genotype data, Coding genotype data
Performing hypothesis test on variants, Producing Manhattan plots
Performing many association tests, QQ-Plots, Multiple hypothesis testing corrections, Principal Components Analysis
Regrssion within R, Adding covariates, Converting data for PLINK
Adding covariates rigerously, Logistic Regression
Implementing the IRLS Algorithm, Making algorithms efficient
Linear mixed models, Implementing EM Algorithm, Timing your code
Explanation of Markov Chains and Monte Carlo Sampling, Implementing MCMC Algorithm