RNA-seq Demystified Workshop

Wrapping up

We hope you now have more familiarity with key concepts, data types, tools, and how they all connect to enable gene expression analysis from bulk RNA-Seq data.

Housekeeping

Please take our optional post-workshop survey (5-10 minutes)
We will email you a link to the final session recordings by next week.
The website/notes for this workshop and the UM Bioinformatics Core Workshop Slack channel will be available.

Looking ahead

Workshop environment

BASH/RStudio workshop compute environment will be available until next Wednesday.
You can download files from the workshop environment from your terminal/command line window as below. (You will need to substitute your actual workshop username and type workshop password when prompted.)
```
mkdir rnaseq-demystified-workshop
cd rnaseq-demystified-workshop
scp -r YOUR_USERNAME@bfx-workshop01.med.umich.edu:"RSD*" .
```
- Note that the full download is about 2-4Gb, so depending on your internet speeds it could take while.

Installing software locally

You can install necessary programs to run programs locally. Note that for typical data, the compute intensive steps (Day 1&2) assume your computer has powerful compute (many CPUs and lots of RAM) and sizable storage capacity. (i.e. It may not be practical to run these on your laptop.)
Installing bioinformatics software is non-trivial and comprehensive instructions to setup a complete compute environment are outside the scope of this workshop. (We are considering offering a Computational Reproducibility workshop that would cover this.) For the intrepid, see relevant links below:

University of Michigan Resources

UM CoderSpaces “office hours” and UM CoderSpaces Slack workspace. (See “Useful Resources” section in above page for instructions on how to join and access the CoderSpaces Slack workspace.)
Upcoming UM Advanced Research Computing workshops.
Advanced Research Computing (ARC) at University of Michigan hosts a high-performance computing (HPC) platform called Great Lakes which combines high-end computers, fast/resilient storage, and pre-installed software. GreatLakes may be a good resource for folks who need to run the more compute intensive steps and a substantial block of compute and storage is subsidized by ARC making it essentially free to many researchers.
- About Great Lakes HPC.
- About the ARC Research Computing Package.
- Videos on getting started with Great Lakes. (available to UM folks)

Training and support

Learning bioinformatic analyses more like a process than a task. Resources to consider:
- UM Bioinformatics Core links to training resources/workshops
- Notes on Bash and R from the recent Computational Foundations Workshop.
- For more intro lessons and workshops in Bash / Git / R / Python : Software Carpentry and the UM Software Carpentry Group.
- For more info on NGS analysis, we can highly recommend training materials from the Harvard Chan Bioinformatics Core.