**Instructor:** Jeff Leek

**Class Website:**

**Resources:**

- Installing R for Windows
- Installing R for Mac
- Rstudio, R project, and Bioconductor
- Rstudio’s cheatsheets

**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.