umierrorcorrect2 0.32.3

Pipeline for analyzing barcoded amplicon sequencing data with Unique Molecular Identifiers (UMI)

UMIErrorCorrect2

A modern, high-performance pipeline for analyzing barcoded amplicon sequencing data with Unique Molecular Identifiers (UMI).

This package is a complete modernization of the original UMIErrorCorrect published in Clinical Chemistry (2022).

Key Features

• High Performance: Parallel processing of genomic regions and fastp-based preprocessing.
• Modern Tooling: Built with typer, pydantic, loguru, and hatch.
• Easy Installation: Fully PEP 621 compliant, installable via pip or uv.
• Comprehensive: From raw FASTQ to error-corrected VCFs and consensus statistics.
• Robust: Extensive test suite and type safety.

Dependencies

Mandatory

• bwa for alignment

Optional

• fastp for preprocessing
• fastqc for quality control
• multiqc for quality control / report aggregation

Fastp is highly recommended, but not mandatory, for preprocessing. If you do not have fastp installed or run with --no-fastp, the pipeline will use cutadapt for adapter trimming only.

The --no-qc flag disables quality control steps. If QC is enabled (default) but fastqc or multiqc are not installed, the pipeline will raise a warning but finish successfully.

Installation

Use uv for lightning-fast installation:

# Installs globally
uv tool install umierrorcorrect2

# Install in your venv
uv pip install umierrorcorrect2

Or standard pip:

pip install umierrorcorrect2

Quick Start

The command-line tool is named umierrorcorrect2. Run the full pipeline on a single sample:

umierrorcorrect2 run \
    -r1 sample_R1.fastq.gz \
    -r2 sample_R2.fastq.gz \
    -r hg38.fa \
    -o results/

Run the pipeline on multiple samples in a folder (searches recursively for FASTQ files):

umierrorcorrect2 run \
    -i folder_with_fastq_files/ \
    -r hg38.fa \
    -o results/

For detailed instructions, see the User Guide or run:

umierrorcorrect2

Documentation

• User Guide: Detailed usage instructions for all commands.
• Docker Guide: Running with containers.
• Implementation Details: Architecture and design overview.

Citation

Osterlund T., Filges S., Johansson G., Stahlberg A. UMIErrorCorrect and UMIAnalyzer: Software for Consensus Read Generation, Error Correction, and Visualization Using Unique Molecular Identifiers, Clinical Chemistry, 2022. doi:10.1093/clinchem/hvac136