From bench to bash — AI & data science for biotech

bench2bash helps wet-lab scientists transition from experimental biology to computational pipelines. We provide tutorials, starter templates, and practical guides for making research reproducible through bioinformatics workflows.

FASTQ is a text-based format for storing both biological sequences (DNA/RNA) and their corresponding quality scores. Each sequence entry contains four lines: header, sequence, separator, and quality scores. It's the standard output format from most sequencing machines.

Reproducible research ensures that scientific findings can be verified and built upon by other researchers. It reduces errors, improves transparency, and accelerates scientific progress by making methods and data accessible.

Our tutorials range from beginner to advanced. Basic tutorials assume no programming background and teach fundamental command-line skills. We provide starter environments with all tools pre-installed to reduce setup friction.

We focus on industry-standard bioinformatics tools including STAR, GATK, DESeq2, Snakemake, and Docker. Our starter templates include pre-configured Conda environments with 50+ essential bioinformatics tools.

Start with our bench2bash-starter template repository, which includes a complete project structure, sample data, and step-by-step workflows. Use 'git clone' to get the template, then follow our getting-started tutorial.

Snakemake is a workflow management system that makes bioinformatics pipelines reproducible and scalable. It automatically handles dependencies, parallelization, and can run on everything from laptops to computing clusters.

All tutorials are tested with real data in controlled environments. We provide pre-built Conda environments, version-controlled dependencies, and include expected outputs. Each tutorial links to a GitHub repository with working code.