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

Project description

UMIErrorCorrect2

PyPI version CI codecov Python 3.10+ License: MIT Ruff

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

  • fastp for preprocessing
  • bwa for alignment

Installation

Use uv for lightning-fast installation:

uv pip install umierrorcorrect2

Or standard pip:

pip install umierrorcorrect2

Quick Start

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

umierrorcorrect batch \
    -r1 sample_R1.fastq.gz \
    -r2 sample_R2.fastq.gz \
    -r hg38.fa \
    -o results/ \
    -ul 12 \
    -sl 16 \
    --fastp

For detailed instructions, see the User Guide or run:

umierrorcorrect --help

Documentation

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

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