mbf-fastq-processor #

The swiss army knife of FastQ (pre-)processing: filter, sample, demultiplex, and report on sequencing reads with explicit, auditable configuration.

Install #

• Pre-compiled releases available for Linux and windows from the releases page
• To build Rust toolchain 1.86+ and zlib / libzstd development files are required
• Alternatively, a nix flake is provided for a fully reproducible environment
• Container image: ghcr.io/tyberiusprime/mbf-fastq-processor:latest (works with Docker or Podman)

Quickstart #

1. Prepare a configuration file input.toml (see example below).
2. Run mbf-fastq-processor template >input.toml to create a configuration file. Edit as necessary.
3. Run mbf-fastq-processor process input.toml (or cargo run --release -- process input.toml during development).
4. Inspect generated FastQ files or HTML/JSON reports (the Inspect step helps surface summaries).

[input]
    read1 = ['myreads.fq']

[[step]]
    action = "Head"
    n = 5000

[[step]]
    action = "Report"
    label = "qc"
    html = true

[output]
    prefix = "output"
    format = "Raw"

mbf-fastq-processor input.toml

Or run the published container (bind-mount your working directory to /work):

docker run --rm -v "$(pwd)":/work ghcr.io/tyberiusprime/mbf-fastq-processor:latest process input.toml

You will find output_read1.fq alongside a sample HTML report at output_qc.html.

Documentation guide #

• Read the Concepts chapter first for a mental model of molecules, segments, and processing steps.
• Dive into the Reference for exhaustive step-by-step configuration details.
• When you are ready to compose real pipelines, consult the (work-in-progress) How-Tos for applied recipes and integrations.

Development #

Looking for validations or edge cases?

We have extensive end-to-end tests in test_cases/ that cover a wide range of scenarios.