| Audience | Computational Skills | Duration |
|---|---|---|
| Biologists | Beginner or intermediate R and/or beginner bash | 2-3 hour workshops |
Use https://tinyurl.com/hcbc-modules to access this page.
This repository has teaching materials for 2-3 hour, hands-on workshops covering a variety of topics related to bioinformatics data analysis. The workshops will lead participants through performing different types of analyses using R/RStudio or Linux.
Some workshops will require a working knowledge of R or completion of the Introduction to R workshop. Other workshops will require a working knowledge of the bash scripting language or completion of the Introduction to Shell workshop.
** NOTE: Detailed information and preparation instructions for each of the workshops can be found by clicking on the workshop links in the table below.
Workshop introduction slides are available here.
Current Workshops (click here for the schedule)
| Lessons | Prerequisites |
|---|---|
| Introduction to R | None |
| Introduction to the tidyverse data science packages and visualizations with ggplot2 | Beginner R or IntroR workshop |
| Gene annotations and functional analysis of gene lists | Beginner R or IntroR workshop |
| Generating research analysis reports with RMarkdown | Beginner R or IntroR workshop |
| Interactive Data Visualization with Shiny in R (with Ista Zahn from the Harvard Business School) | Beginner R or IntroR workshop |
| Lessons | Prerequisites |
|---|---|
| Introduction to Python | None |
| Visualization in R | Beginner R or IntroR workshop |
| Functional analysis of gene lists | Beginner R or IntroR workshop |
| Introduction to the command-line interface | None |
| Intermediate bash | Beginner bash or Intro to the command-line interface |
| Version control using Git and Github | Beginner bash or Intro to the command-line interface |
| Accessing genomic reference and experimental sequencing data | Beginner bash or Intro to the command-line interface |
| Exploring genomic variants using GEMINI | Beginner bash or Intro to the command-line interface |
| Planning a bulk RNA-seq analysis: Part I | None |
| Planning a bulk RNA-seq analysis: Part II | None |
| Make your (RNA-seq) data analysis reproducible- Taught by Julie Goldman from Countway Library | None |
| Improving your (RNA-seq) data analysis using version control (Git) | None |
These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.