Introduction to the tutorials

Welcome to the tutorials! Here we will learn how to make a computational research project reproducible using the tools:

• Conda
• Snakemake
• Git
• R Markdown
• Jupyter
• Docker

The case study

We will be running a small bioinformatics project as a case study, and use that to exemplify the different steps of setting up a reproducible research project. To give you some context, the study background and analysis steps are very briefly described below.

Background

The data is taken from Osmundson, Dewell, and Darst (2013), who have studied methicillin-resistant Staphylococcus aureus (MRSA). MRSA is resistant to broad spectrum beta-lactam antibiotics and lead to difficult-to-treat infections in humans. Lytic bacteriophages have been suggested as potential therapeutic agents, or as the source of novel antibiotic proteins or peptides. One such protein, gp67, was identified as a transcription-inhibiting transcription factor with an antimicrobial effect. To identify S. aureus genes repressed by gp67, the authors expressed gp67 in S. aureus cells. RNA-seq was then performed on three S. aureus strains:

• RN4220 with pRMC2 with gp67
• RN4220 with empty pRMC2
• NCTC8325-4

Analysis

The graph below shows the different steps of the analysis that are included in this project.

• The input files are:
  • RNA-seq raw data (fastq files) for the three strains
  • S. aureus genome sequence (fasta file)
  • S. aureus genome annotation (gff file)

• get_genome_fasta - Download the genome file.
• index_genome - Index the genome, required for the alignment step, using the software Bowtie2.
• get_SRA_by_accession - Download the RNA-seq raw data for the three strains from the Sequence Read Archive (SRA).
• fastqc - Run quality control on each of the RNA-seq fastq files, using the software FastQC.
• multiqc - Summarize the QC.
• align_to_genome - Align the RNA-seq data from the three strains to the indexed genome, using the software Bowtie2.
• sort_bam - Sort the alignment files by genome coordinate, using the software Samtools.
• get_genome_gff3 - Download the genome annotation file.
• generate_count_table - Calculate gene expression by counting aligned reads per gene, using the software HTSeq-count.
• generate_rulegraph - Generate the workflow overview figure shown above.
• make_supplementary - Produce the supplementary materials section using data from the QC, gene counting and the graph figure.

Setup

For Mac / Linux users

Clone the git/bitbucket repository containing all files you will need for completing the tutorials. First, cd into a directory on your computer (or create one) where it makes sense to download the course directory.

cd /path/to/your/directory
git clone https://bitbucket.org/scilifelab-lts/reproducible_research_course.git
cd reproducible_research_course

For Windows users

There are several different ways to run the course material on a Windows computer. Neither is perhaps optimal, and the material itself has not been adapted specifically for Windows. Nevertheless, in principle everything should be possible to run. A few ways you could setup:

• Run as Linux through a virtual machine (and see the Linux setup above)
• Use the Windows 10 PowerShell, install git and clone the course repository (see the Mac/Linux setup above)
• Use the Linux Bash Shell on Windows 10 (see below) Recommended for the course
• Run the course in a Docker container (see below)

Running in the Linux Bash Shell on Windows 10

For the difference between the Linux Bash Shell and the PowerShell on Windows 10, see e.g. this article.

Install Bash on Windows 10, follow the instructions at e.g. one of these resources:

• https://docs.microsoft.com/en-us/windows/wsl/install-win10
• https://www.howtogeek.com/249966/how-to-install-and-use-the-linux-bash-shell-on-windows-10/
• https://itsfoss.com/install-bash-on-windows/

Using Docker to run the course

Alternatively, you could use Docker to run the course in a Docker container. First, cd into a directory on your computer (or create one) where it makes sense to download the course directory. Install Docker by following the instructions in the Docker tutorial. Then run:

cd c:/my_dir
docker run -it -p 8888:8888 -v /c/my_dir:/course/ scilifelablts/reproducible_research_course_slim:course_1905

This will start an isolated container running Linux, where the directory c:/my_dir is mounted (i.e. you can access the files in this Windows directory within the Linux container, and files edited or created within the Linux container will appear in this Windows directory). Note that the idea is that you should edit files in the mounted c:/my_dir using an editor in your normal OS, say Notepad in Windows. The terminal in the container is for running stuff, not editing.

You should now be at a terminal in the Docker container. Now clone the git/bitbucket repository containing all the files you will need for the tutorials.

git clone https://bitbucket.org/scilifelab-lts/reproducible_research_course.git
cd reproducible_research_course

Don't worry if you feel that this Docker stuff is a little confusing, it will become clearer in the Docker tutorial. However, the priority right now is just to get it running so that you can start working.

The tutorials

The figure below gives an overview of the six available tutorials, a very brief description of their main purpose, and the suggested order to do them. However, each tutorial is made so that it can be completed independently of the other tutorials. It is therefore perfectly possible to choose a different order, or a subset of tutorials that suits your interests. Under the main figure there is a list of a few suggested alternative tutorial orders. You find the tutorials in the menu to the left!

Note that running through the tutorials will involve installing several tools, which in turn will create quite a lot of files on your computer. In order to remove any traces of these, after completing the tutorials, please refer to the Take down section.