Installation
Install Julia
To install Julia, follow the Getting Started instructions.
Install Quarto (optional)
These tutorials are written in Quarto. You don’t need Quarto if you only want to play with the notebooks, but you will need it if you want to reprodcue this website locally. See the Get Started page for installation instructions.
Install the Julia extension for your favourite editor/IDE (optional)
Extensions or plugins for VS Code, Emacs, and VIM are linked from the Julia homepage
Install IJulia
To run the tutorial notebooks, you need IJulia. If you installed Quarto, follow these instructions to make sure Quarto can use IJulia to render documents with embedded Julia code.
Install BioFindr
BioFindr is a registered Julia package. To install it, open a Julia console and enter the Pkg REPL by pressing ]
from the Julia REPL. Then:
> add BioFindr pkg
See the Pkg documentation for more information. If you’re new to using Pkg, Julia’s package manager, see the Getting Started notes.
BioFindr is still under development and new features are added regularly. Make sure to update your installation regularly:
> up BioFindr pkg
Install the BioFindrTutorials repository
The BioFindrTutorials repository uses DrWatson to make a reproducible scientific project named
BioFindrTutorials
To (locally) reproduce this project, do the following:
Download this code base. Notice that raw data are not in
julia> using Pkg julia> Pkg.add("DrWatson") # install globally, for using `quickactivate` julia> Pkg.activate("path/to/this/project") julia> Pkg.instantiate()
This will install all necessary packages for you to be able to run the scripts and everything should work out of the box, including correctly finding local paths.
You may notice that most scripts start with the commands:
using DrWatson
@quickactivate "BioFindrTutorials"
which auto-activate the project and enable local path handling from DrWatson.
Download and preprocess data
The scripts
folder of the project contains a number of files named process_data_*
. After downloading the initial data files (see below), you can then run the script to produce processed data files in the Apache Arrow format, which will be stored in the exp_pro
folder.
GEUVADIS data
Download preprocessed data files from the GEUVADIS study.
Save all files in the folder
exp_raw/findr-data-geuvadis
.Concatenate the transcript files:
$ cat dt1.csv.gz dt2.csv.gz > dt.csv.gz
Unzip all
.gz
files.Create a folder
exp_pro/findr-data-geuvadis
(sorry, not very clean that this isn’t automated).Run the script
process_data_findr-data-geuvadis.jl
. You can either run it from the command line:$ julia scripts/process_data_findr-data-geuvadis.jl
or open the file and run it interactively in your editor/IDE of choice. See Running Code for more information about how to this in VS Code.
Verify that the directory
exp_pro/findr-data-geuvadis
contains matched.arrow
files for each.csv
file in theexp_raw/findr-data-geuvadis
folder.
Run the tutorials
You are now all set up to run the tutorials. You can either work directly with the *.qmd
files in the website
folder, or use the jupyter notebooks (*.ipynb
files) in the notebooks
folder. Make sure to have IJulia installed if using the latter option.