Instructor: Jeff Leek
Class Website:
Resources:
Course Materials
| Week/Lecture | Lecture | Video | Notes | Code |
|---|---|---|---|---|
| 0/1 | Welcome | Google Slides pdf | ||
| 0/2 | What is statistics? | Google Slides pdf | ||
| 0/3 | Finding statistics you can trust | Google Slides pdf | ||
| 0/4 | Getting help | Google Slides pdf | ||
| 0/5 | What is data? | Google Slides pdf | ||
| 0/6 | Representing data | Google Slides pdf | ||
| — | — | — | — | — |
| 1/1 | Week 1 Introduction | Google Slides pdf | ||
| 1/2 | Reproducible research | Google Slides pdf | ||
| 1/3 | Achieving reproducible research | Google Slides pdf | NA | |
| 1/4 | R markdown | html | R markdown R code | |
| 1/5 | The three tables in genomics | Google Slides pdf | ||
| 1/6 | The three tables in genomics (in R) | html | R markdown R code | |
| 1/7 | Experimental Design: variability, replication, and power | Google Slides pdf | NA | |
| 1/8 | Experimental Design: confounding and randomization | Google Slides pdf | ||
| 1/9 | Exploratory Analysis | Google Slides pdf | ||
| 1/10 | Exploratory Analysis in R | html | R markdown R code | |
| 1/11 | Data transforms | html | R markdown R code | |
| 1/12 | Clustering | Google Slides pdf | ||
| 1/13 | Clustering in R | html | R markdown R code | |
| — | — | — | — | — |
| 2/1 | Week 2 Introduction | Google Slides pdf | ||
| 2/2 | Dimension reduction | Google Slides pdf | ||
| 2/3 | Dimension reduction (in R) | html | R markdown R code | |
| 2/4 | Pre-processing and normalization | Google Slides pdf | ||
| 2/5 | Quantile normalization (in R) | html | R markdown R code | |
| 2/6 | The linear model | Google Slides pdf | html R markdown R code | |
| 2/7 | Linear models with categorical covariates | Google Slides pdf | ||
| 2/8 | Adjusting for covariates | Google Slides pdf | html R markdown R code | |
| 2/9 | Linear regression in R | html | R markdown R code | |
| 2/10 | Many regressions at once | Google Slides pdf | ||
| 2/11 | Many regressions in R | html | R markdown R code | |
| 2/12 | Batch effects and confounders | Google Slides pdf | ||
| 2/13 | Batch effecs in R | html | R markdown R code | |
| — | — | — | — | — |
| 3/1 | Week 3 Introduction | Google Slides pdf | ||
| 3/2 | Logistic regression | Google Slides pdf | ||
| 3/3 | Regression for counts | Google Slides pdf | ||
| 3/4 | GLMs in R | html | R markdown R code | |
| 3/5 | Inference | Google Slides pdf | ||
| 3/6 | Null and alternative hypotheses | Google Slides pdf | ||
| 3/7 | Calculating statistics | Google Slides pdf | ||
| 3/8 | Comparing models | Google Slides pdf | html R markdown R code | |
| 3/9 | Calculating statistics in R | html | R markdown R code | |
| 3/10 | Permutation | Google Slides pdf | ||
| 3/11 | Permutation in R | html | R markdown R code | |
| 3/12 | P-values | Google Slides pdf | ||
| 3/13 | Multiple testing | Google Slides pdf | ||
| 3/14 | P-values and multiple testing in R | html | R markdown R code | |
| — | — | — | — | — |
| 4/1 | Week 4 Introduction | Google Slides pdf | ||
| 4/2 | Gene set analysis | Google Slides pdf | ||
| 4/3 | More enrichment | Google Slides pdf | ||
| 4/4 | Gene set analysis in R | html | R markdown R code | |
| 4/5 | The process for RNA-seq | Google Slides pdf | ||
| 4/6 | The process for Chip-Seq | Google Slides pdf | ||
| 4/7 | The process for DNA methylation | Google Slides pdf | ||
| 4/8 | The process for GWAS/WGS | Google Slides pdf | ||
| 4/9 | Combining data types (eQTL) | Google Slides pdf | ||
| 4/10 | eQTL in R | html | R markdown R code | |
| 4/11 | Researcher degrees of freedom | Google Slides pdf | Interesting example | |
| 4/12 | Inference vs. prediction | Google Slides pdf | ||
| 4/13 | Knowing when to get help | Google Slides pdf | R markdown | |
| 4/14 | Course Wrap-up | Google Slides pdf | ||
| — | — | — | — | — |
Course R package
You can get all of the code used in the class by installing the R package:
source("http://bioconductor.org/biocLite.R")
biocLite("devtools") # only if devtools not yet installed
biocLite("jtleek/genstats",ref="gh-pages")You can see the list of lecture notes and open them using the vignette command:
library(genstats)
vignette(package="genstats")
vignette("01_13_clustering")Miscellaneous
Feel free to submit typos/errors/etc via the github repository associated with the class: https://github.com/jtleek/genstats_site
This web-page is modified from Andrew Jaffe’s Summer 2015 R course, which also has great material if you want to learn R.
This page was last updated on 2015-09-07 07:37:18 Eastern Time.