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Lab 9 NOTES - GGG 201b, March 10th, 2023

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Permanent link on GitHub: lab-9.md

Friday Lab links

Setting things up on farm

Today we're going to do things a little differently. Let's hope it all works!

We need to install a bunch of things before running RStudio today.

So, ssh into farm and do an srun:

srun -p high2 --time=3:00:00 --nodes=1 \
    --cpus-per-task 4 --mem 10GB --pty /bin/bash

Clone the RNAseq github repo into ``~/lab9-rnaseq`:

git clone https://github.com/ngs-docs/2020-ggg-201b-rnaseq ~/lab9-rnaseq
cd ~/lab9-rnaseq

Install a bunch of R software into a conda environment called rnaseq:

mamba env create -n rnaseq -f binder/environment.yml

(This will take a while!)

Activate that conda environment:

mamba activate rnaseq

Activate the RStudio server module:

module load rstudio-server/2022.12.0

Run rstudio-launch:

rstudio-launch

and follow the instructions to set up your ssh tunneling connection and log in to the RStudio Server.

Double check things

In your Console window for RStudio Server, you should be able to scroll up and see that you're using the version of R that was installed by mamba:

R version 4.0.5 (2021-03-31) -- "Shake and Throw" Copyright (C) 2021 The R Foundation for Statistical Computing Platform: x86_64-conda-linux-gnu (64-bit)

Run the RNAseq workflow at the command line

From within RStudio, start a terminal and activate your conda environment:

mamba activate rnaseq

Change to the lab 9 directory we created above:

cd ~/lab9-rnaseq

Now, run the snakemake workflow:

snakemake -j 4 --use-conda

@@examine files

Load the RMarkdown document

Open the rnaseq-workflow.Rmd file in lab9-rnaseq.

Select knit, knit to HTML.

(Say "yes" to installing new RMarkdown packages.)

It may fail the first time; if so, just rerun things by selecting knit, knit to HTML.