| 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.
| Topic and Link(s) to lessons | Prerequisites | Date | Registration |
|---|---|---|---|
| Introduction to Shell | None | 1/18/2023 | Closed |
| Intermediate Shell | Introduction to Shell | 2/15/2023 | Closed |
| Advanced Shell | Intermediate Shell | 3/13/2023 | Closed |
| Git/Github | Introduction to Shell | 4/19/2023 | Closed |
| ML4Bio | None | 5/17/2023 | Closed |
| Basics of Python | None | 6/21/2023 | Closed |
| R Basics | None | 7/19/2023 | Sign up! |
| R Basics Practice | R Basics or Online R course - Harvard Catalyst | 8/16/2023 | Sign up! |
| Publication Perfect: Part I | R Basics or Completion of the Intro to R online resource | 9/20/2023 | Sign up! |
| Publication Perfect: Part II | Publication Perfect: Part I | 10/18/2023 | Sign up! |
| Rmarkdown | R Basics or Online R course - Harvard Catalyst | 11/15/2023 | Sign up! |
| Topic and Link(s) to lessons | Prerequisites |
|---|---|
| Introduction to R | None |
| Tidyverse | Beginner R or Intro to R workshop |
| Introduction to R Practical | Beginner R or Completion of the Intro to R online resource |
| Gene annotations and functional analysis of gene lists | Beginner R or Intro to R workshop |
| Generating research analysis reports with RMarkdown | Beginner R or Intro to R workshop |
| Interactive Data Visualization with Shiny in R (with Ista Zahn from the Harvard Business School) | Beginner R or Intro to R workshop |
| Publication Perfect: Part I | Beginner R or Completion of the Intro to R online resource |
| Publication Perfect: Part II | Publication Perfect: Part I |
| Functional analysis of gene lists | Beginner R or Intro to R workshop |
| Topic and Link(s) to lessons | Prerequisites |
|---|---|
| Introduction to the command-line interface | None |
| Intermediate bash | Beginner shell or Intro to the command-line interface |
| Version control using Git and Github | Beginner shell or Intro to the command-line interface |
| Accessing genomic reference and experimental sequencing data | Beginner shell or Intro to the command-line interface |
| Exploring genomic variants using GEMINI | Beginner shell or Intro to the command-line interface |
| Topic and Link(s) to lessons | Prerequisites |
|---|---|
| Introduction to Python | None |
| 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.
A lot of time and effort went into the preparation of these materials. Citations help us understand the needs of the community, gain recognition for our work, and attract further funding to support our teaching activities. Thank you for citing the corresponding course (as suggested in its "Read Me" section) if it helped you in your data analysis.