README.md

Snakeflows

Collective Snakemake workflows for easy and reproducable NGS data analysis.

Workflows may contain modified parameters, Please look at snakemake files before use.

RNA-Seq Analysis

Currct workflows

• STAR-Cufflinks
• Salmon

Workflows are making in progress. I will add more downstreem tools as go along. You have an workflow in mind too add! Requet it here -

Quick start

Pre-requirements

You need to have Python3 installed in your system with conda enabled.

Install needed tools with following command

conda env create -f environment.yml
conda activate snakeflows

Downlorad sample data to test the workflow:

wget https://www.dropbox.com/s/bnvjbhq4970pvg8/sample_data.tar.gz?dl=0

1. Prepare samples directory properly

Before you run write_sample_to_json.py, samples directory arangement and it's naming needs to be proper such that it can be read by the script and call furthere in snakemake files.

Something like this:

samples
├── SET1_dummy
│   ├── SET1_dummy_R1.fastq.gz
│   └── SET1_dummy_R2.fastq.gz
└── SET3_dummy
    ├── SET3_dummy_R1.fastq.gz
    └── SET3_dummy_R2.fastq.gz

2. Generate samples.json file

This will be used to automatic detect samples names and call them in snakemake files.

python3 write_sample_to_json.py --fastq_dir full_path_to_samples_directory

3. Run Workflows

First Edit the config.yml files inside workflow directory with required full paths.

Then simply call snakemake from workflow directory (With additional parameters if required)

snakemake --cores 12

Additional

For checking workflow and debug

snakemake -np

Visualise the workflow

snakemake --forceall --dag | dot -Tpng | display

Upcoming additons:

• Docker integration
• Streamlined html reports
• Log files with timestamp
• Making it more modular with .smk files