Dry-Bench-Skills-Recap.md

Dry Bench Skills for Researchers Review

Today, this is our last class, and we want to begin with a small recap and an illustration of an end-to-end final result.

A Paper in BioRxiv, with code for the nextflow workflow on GitHub and all analyses in jupyter notebooks and even an example of how to run a jupyter notebook using a tool called papermill.

The goal of this course was to put parenthesis around the dry bench skills required to be a successful researcher with regards to being reproducible. You are now part of the group that will be in a position to ensure your science is reproducible.

As with all things, the best way to advance is to practice these skills.

Thank you for being part of this pilot. We aren't done yet, we will have each of you execute an RNA-seq example forked from nf-core.

What we have done

Day 1

1. We began by introducing you to using command-line
2. We then addressed reading data and plotting in R

Day 2

1. We discussed version control and introduced you to Git and GitHub
2. Introduced you to forking a repository and how to push your changes back into a repository
3. Giving you a chance to add and push your changes back to the main repository

Day 3

1. We introduced you to conda for managing your environment and dependencies
2. We used these environments as we introduced you to containers

Day 4

We focused the entire day on learning the workflow language nextflow day

Day 5

Today, we focused on putting it all together for an end-to end solution, executing a community-based standard nextflow workflow from nf-core