TSSpy: Python CLI for TSS Analysis

TSSpy is a Python command-line tool designed for the analysis of transcription start site (TSS) data. Inspired by the TSSr (R/Bioconductor) package (https://github.com/Linlab-slu/TSSr)

Features

• Main-command + subcommand structure for modularity and scalability
• Multi-processing support for fast analysis
• Compatible with BAM and TSS table input formats
• Supports BigWig/BedGraph export for genome browser visualization
• Clustering, correlation analysis, and promoter identification
• Suitable for large-scale high-throughput sequencing data
• Clean codebase for easy secondary development

Installation

Using pip

It is recommended to use Python 3.8 or above.

pip install tsspy

After installation, you can use the tsspy command directly from the terminal.

Using conda (recommended)

conda create -n tsspy python=3.8
conda activate tsspy
conda install -c bioconda -c conda-forge tsspy

Dependencies

• Python >= 3.8
• typer (automatically installs click as a dependency)
• pysam
• pandas
• numpy
• biopython
• pyBigWig

Quick Start

Command Usage

After installation, you can use TSSpy in two ways:

1. Direct command (recommended):

   tsspy [command] [options]

2. Module invocation (for development):

   python -m TSSpy.main [command] [options]

All examples below use the direct command format.

1. TSS Calling

Extract TSS from BAM files:

tsspy tssCalling -i sample1.bam -o sample1.TSS.tsv

Multiple BAM files in parallel:

tsspy tssCalling -i sample1.bam -i sample2.bam -o all.TSS.tsv -n "sample1 sample2"

2. TSS Clustering

Cluster TSSs to infer core promoters:

tsspy clustering -i all.TSS.tsv -o all.TSS.clustered.tsv -s sample1

3. Generate BigWig/BedGraph Files

Create visualization files for genome browsers:

# Generate bigWig files (requires chromosome sizes)
tsspy bigwig --input all.TSS.tsv --output-prefix all_samples --format bigwig --reference genome.fa --process

# Generate bedGraph files
tsspy bigwig --input all.TSS.tsv --output-prefix all_samples --format bedgraph

4. Correlation Analysis

Calculate correlations between samples:

tsspy correlation --input all.TSS.tsv --output correlation_matrix.tsv

5. Plot TSS Data

Generate visualization plots:

tsspy plot --help

6. Gene Assignment (Under Development)

tsspy geneAssign --help

Subcommands

• tssCalling: Identify TSSs from BAM files and output a TSS table
• clustering: Cluster TSSs to infer core promoters
• bigwig: Generate BigWig/BedGraph files for genome browser visualization
• correlation: Calculate correlations between TSS samples
• plot: Generate plots and visualizations for TSS data
• geneAssign: Assign TSS clusters to genes (under development)

Extensibility

• To add a new feature, simply create a new subcommand module in TSSpy/ and register it in main.py
• Shared utility functions can be placed in TSSpy/utils.py
• Built with modern CLI frameworks

Contributing

Contributions, issues, and feature requests are welcome!

License

MIT