Pipeline for analyzing barcoded amplicon sequencing data with Unique Molecular Identifiers (UMI)
Project description
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, andhatch. - Easy Installation: Fully PEP 621 compliant, installable via
piporuv. - Comprehensive: From raw FASTQ to error-corrected VCFs and consensus statistics.
- Robust: Extensive test suite and type safety.
Dependencies
fastpfor preprocessingbwafor 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
- User Guide: Detailed usage instructions for all commands.
- Implementation Details: Architecture and design overview.
- Docker Guide: Running with containers.
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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