BOTAS

Bacterial Operon-Aware Transcriptome Alignment System

BOTAS is a bacterial RNA-seq analysis framework that integrates read alignment, gene quantification, operon inference, and operon-level quantification within a unified Python package. It is specifically designed for bacterial transcriptomes, providing native support for circular genomes, operon-aware analyses, and strand-specific expression profiling.

Unlike general-purpose RNA-seq aligners developed primarily for eukaryotic transcriptomes, BOTAS addresses the unique characteristics of bacterial genomes, including dense gene organization, polycistronic transcription, operon architecture, and circular chromosomes.

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Key Features

• Seed-and-extend alignment engine optimized for bacterial genomes
• Native support for circular chromosomes and plasmids
• Paired-end and single-end read alignment
• Strand-aware gene expression quantification
• Gene-level and operon-level expression quantification
• Operon inference from aligned reads
• Operon-aware transcriptome analysis
• Optional rRNA filtering
• Parallel execution for scalable performance
• Modular and extensible Python architecture

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Why BOTAS?

Most RNA-seq aligners were designed for eukaryotic transcriptomes and assume splicing, large introns, and linear chromosomes. These assumptions are inappropriate for bacterial transcriptomes, which are characterized by:

• Densely packed genes
• Polycistronic transcripts organized into operons
• Circular chromosomes and plasmids
• Strong dependence on strand-specific transcription

BOTAS addresses these challenges through native circular-genome support, operon-aware analysis, strand-specific quantification, circular insert-size validation, and integrated gene and operon quantification within a single framework.

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Installation

Install from PyPI

pip install botas

Install the latest development version

pip install git+https://github.com/clabe-wekesa/botas.git

Install from source

git clone https://github.com/clabe-wekesa/botas.git
cd botas
pip install .

Development installation

pip install -e ".[dev]"

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Quick Start

Paired-end alignment

botas align \
    -r reference.fasta \
    -1 reads_R1.fastq \
    -2 reads_R2.fastq \
    -o aligned.bam

Single-end alignment

botas align \
    -r reference.fasta \
    -U reads.fastq \
    -o aligned.bam

Gene quantification

botas quantify \
    -b aligned.bam \
    -g genes.gff \
    -o gene_counts.tsv

Supported features include:

• Strand-specific counting
• MAPQ filtering
• Multi-mapper handling
• TPM and RPKM calculation
• Multi-BAM count matrix generation

Operon inference

botas getOperons \
    -b aligned.bam \
    -g genes.gff \
    -o operons.tsv

Operon inference integrates:

• Intergenic distance
• Strand consistency
• Coverage similarity
• Paired-end support
• Consensus-based merging

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Architecture

botas/
├── cli/          # Command-line interface
├── core/         # Alignment engine
├── data/         # Reference resources
├── io/           # FASTQ, BAM and reference handling
├── operons/      # Operon inference
├── quantify/     # Gene and operon quantification
└── rrna/         # rRNA detection and filtering

The alignment engine implements:

• K-mer indexing
• Seed clustering
• Edit-distance extension using edlib
• CIGAR reconstruction
• Mapping quality estimation
• Circular coordinate normalization

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Design Principles

BOTAS is designed to provide:

• Accurate bacterial RNA-seq alignment
• Native support for circular genomes
• Reproducible gene and operon quantification
• Transparent and interpretable alignment scoring
• Modular architecture for method development and extension
• Integration of alignment and operon-level analyses within a unified workflow

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Requirements

Required

• Python ≥ 3.10
• pysam
• edlib
• biopython

Optional

• tqdm (progress display)

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Documentation

Command-line help is available through:

botas --help
botas align --help
botas quant --help
botas getOperons --help

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Citation

If you use BOTAS in your research, please cite:

Wekesa, C. S. BOTAS: Bacterial Operon-Aware Transcriptome Alignment System.

Citation details will be updated following publication.

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License

BOTAS is distributed under the MIT License. See the LICENSE file for details.

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Author

Clabe Simiyu Wekesa

GitHub: https://github.com/clabe-wekesa