SnakeAltPromoter 1.0.4

A Snakemake pipeline for alternative promoter analysis

🧬 SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis

SnakeAltPromoter is a Snakemake-based pipeline for streamlined, reproducible, and scalable analysis of alternative promoter usage from RNA-seq or CAGE data. It integrates all major steps—from raw read preprocessing to promoter-level quantification and differential analysis—using state-of-the-art tools.

🧭 Workflow Overview

Below is the schematic overview of the SnakeAltPromoter pipeline, as shown in our paper:

Figure 1. Overview of the SnakeAltPromoter pipeline, showing genome setup, RNA-seq/CAGE processing, promoter quantification, classification, and differential promoter usage analysis.

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✳️ Key Features

• End-to-end automation of alternative promoter analysis from FASTQ to results.

• Integrated QC and preprocessing via FastQC, TrimGalore, STAR, and MultiQC.

• Supports multiple promoter quantification tools:

  • ProActiv
  • DEXSeq
  • Salmon

• Built-in differential analysis using DESeq2 and ProActiv modules.

• Fully modular, reproducible, and scalable—ideal for large multi-sample RNA-seq datasets.

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🧩 Installation

1. Install via Conda (Recommended)

# Create and activate environment
conda create -n SnakeAltPromoter -c bioconda SnakeAltPromoter
conda activate SnakeAltPromoter

2. Install via Pip

pip install --user --no-cache-dir SnakeAltPromoter

3. Manual Installation (Build from Source)

git clone https://github.com/YidanSunResearchLab/SnakeAltPromoter.git
cd SnakeAltPromoter
conda create -n SnakeAltPromoter -c conda-forge python
conda activate SnakeAltPromoter
pip install .

4. Verify Installation

Snakealtpromoter --help

If successful, usage instructions and command-line options will be displayed.

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🖥️ Optional: Launch GUI

For a graphical interface:

sap-ui

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🧪 Minimal Test Case

Example human chr22 genome fasta and gtf files are available in the snakealtpromoter/data/ directory. Example RNA-seq data are available in the snakealtpromoter/data/ directory.

1. Genome Setup

git clone https://github.com/YidanSunResearchLab/SnakeAltPromoter.git
cd SnakeAltPromoter
Genomesetup \
  --organism hg38 \
  --organism_fasta "$(pwd)/snakealtpromoter/data/hg38.fa" \
  --genes_gtf "$(pwd)/snakealtpromoter/data/hg38.gtf" \
  -o ./genome \
  --threads 30

2. Run Test Analysis

git clone https://github.com/YidanSunResearchLab/SnakeAltPromoter.git
cd SnakeAltPromoter
Snakealtpromoter \
  -i "$(pwd)/snakealtpromoter/data" \
  --genome_dir "$(pwd)/genome" \
  -o test_output \
  --threads 30 \
  --organism hg38 --trim \
  --sample_sheet "$(pwd)/snakealtpromoter/data/samplesheet/samplesheet.tsv"

Output directory structure is described in the documentation:

• Genomesetup
• Snakealtpromoter

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📊 Reproduce Results from the Paper

To reproduce analyses in the SnakeAltPromoter manuscript:

1. Download the GENCODE v46 genome FASTA and GTF from GENCODE.
2. Retrieve heart RNA-seq and CAGE data from GSE147236 using fastq-dump.

1. Genome Setup

Genomesetup \
  --organism hg38 \
  --organism_fasta /Absolute/path/to/genome.fa \
  --genes_gtf /Absolute/path/to/genes.gtf \
  -o /Absolute/path/to/genome \
  --threads 30

2. RNA-seq Processing

git clone https://github.com/YidanSunResearchLab/SnakeAltPromoter.git
cd SnakeAltPromoter
Snakealtpromoter \
  -i /Absolute/path/to/heart_RNAseq/ \
  --genome_dir /Absolute/path/to/genome \
  -o heart_RNAseq_output \
  --threads 30 \
  --organism hg38 --trim \
  --sample_sheet "$(pwd)/snakealtpromoter/data/samplesheet/Heart_RNAseq.tsv"

3. CAGE Processing

git clone https://github.com/YidanSunResearchLab/SnakeAltPromoter.git
cd SnakeAltPromoter
Snakealtpromoter \
  -i /Absolute/path/to/heart_CAGE/ \
  --genome_dir /Absolute/path/to/genome \
  -o heart_CAGE_output \
  --threads 30 \
  --organism hg38 \
  --sample_sheet "$(pwd)/snakealtpromoter/data/samplesheet/Heart_CAGE.tsv" \
  --method cage --reads single

4. Compare with Published Results

Supplementary Table	Description
Table 1	Comprehensive promoter coordinates
Table 2	Promoter classifications (major/minor) by ProActiv, Salmon, DEXSeq, and CAGE
Table 3	Promoter counts across samples
Table 4	Differential promoter activity (healthy vs. failure) across tools

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🚀 Quick Start for your own genome and sequencing data

Step 1. Genome Setup

Prepare genome indices and promoter annotations:

Genomesetup \
  --organism hg38 \
  --organism_fasta /Absolute/path/to/genome.fa \
  --genes_gtf /Absolute/path/to/genes.gtf \
  -o /Absolute/path/to/genome \
  --threads 30

Step 2. Process RNA-seq Data

Run alternative promoter analysis:

Snakealtpromoter \
  -i /Absolute/path/to/input_fastqs/ \
  --genome_dir /Absolute/path/to/genome \
  -o ./output/ \
  --threads 30 \
  --organism hg38 --trim \
  --sample_sheet /Absolute/path/to/samplesheet.tsv \
  --method cage --reads single   # Add these only for CAGE data

For detailed documentation, see:

• Genomesetup
• Snakealtpromoter

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🤝 Contributing

Contributions are welcome! Please open an issue or submit a pull request via GitHub.

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🧾 Citation

If you use SnakeAltPromoter, please cite:

Tan J. et al. (2025). SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis. bioRxiv. https://doi.org/10.1101/2025.08.16.669128

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⚖️ License

See the LICENSE file for details.