ASO Off-Target Checker

A Flask web application for checking antisense oligonucleotide (ASO) off-target effects using NCBI BLAST.

This tool was based on the report entitled In silico off-targets analysis for PrP-lowering divalent siRNA 2439-exNA of Eric Vallabh Minikel, PhD.

Features

• Sequence Analysis: Check ASO sequences for potential off-target binding
• Multiple Species Support:
  • Human (Homo sapiens, taxid: 9606)
  • Mouse (Mus musculus, taxid: 10090)
  • Rat (Rattus norvegicus, taxid: 10116)
• Customizable Parameters: Adjustable E-value and mismatch thresholds
• Downloadable Results: Export results in tab-delimited text format
• User-Friendly Interface: Clean, responsive web interface with collapsible advanced options

Prerequisites

Before running the application, ensure you have:

1. NCBI BLAST+ installed locally

   • Download from: https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGETYPE=BlastDocs&DOCTYPE=Download

2. BLAST Databases set up:

   • Requires refseq_select_rna database
   • Can be downloaded using NCBI's update_blastdb.pl script

3. Python 3.7+ with the following packages (install via requirements.txt)

Installation

1. Clone this repository: bash git clone https://github.com/yourusername/aso-offtarget-checker.git cd aso-offtarget-checker

2. Install Python dependencies: bash pip install -r requirements.txt

3. Set up BLASTDB environment variable (critical for BLAST to find databases): bash export BLASTDB=/path/to/your/blast/databases Note: Add this to your shell configuration file (e.g., .bashrc, .zshrc) to make it persistent.

4. Verify BLAST installation: bash blastn -version

Usage

Running the Application

Start the Flask development server: bash python app.py

The application will be available at: http://localhost:8080/check-aso

Using the Web Interface

1. Enter ASO Sequence:

   • Input your ASO sequence (DNA only, ACGTN characters)
   • Default example sequence provided

2. Select Species:

   • Choose from Human, Mouse, or Rat

3. Advanced Options (click to expand):

   • E-value threshold: Default = 1000 (higher values return more results)
   • Max mismatches: Default = 4 (maximum allowed mismatches)

4. Run Analysis:

   • Click "Run BLAST" to start the search
   • Results typically appear within seconds to minutes depending on query length

5. Download Results:

   • After analysis, click "Download Results" to save as text file
   • Filename includes species and timestamp for easy identification

Configuration

Environment Variables

For proper BLAST operation, these environment variables may need configuration:

```bash

Path to BLAST databases (REQUIRED)

export BLASTDB=/path/to/blast/databases

Optional: Increase number of threads for BLAST

export BLASTNUM_THREADS=4 ```

Application Settings

Modify app.py for these options:

• Change default port (currently 8080)
• Adjust default sequence parameters
• Modify BLAST command options (e.g., -num_alignments)

Troubleshooting

Common Issues

1. BLAST Database Not Found: Error: BLAST database not found

   • Solution: Verify BLASTDB environment variable points to correct directory
   • Ensure required databases (refseqselectrna) are present

2. Invalid Sequence Error:

   • Only ACGTN characters allowed
   • Sequences are automatically converted to uppercase

3. No Results Found:

   • Try increasing E-value threshold
   • Increase maximum allowed mismatches
   • Verify your sequence doesn't contain invalid characters

Technical Details

BLAST Parameters

The application uses these BLASTN parameters by default: bash blastn \ -task blastn-short \ -db refseq_select_rna \ -outfmt 5 `# XML file` \ -evalue [user_specified] \ -num_alignments 5000 \ -taxids [selected_species_taxid]

Data Processing

1. XML output from BLAST is parsed using Python's ElementTree
2. Results are filtered by:
   • Frame = 1 (forward strand only)
   • User-specified mismatch threshold
3. Alignment visualization shows:
   • Query sequence
   • Midline (match indicators)
   • Hit sequence

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• NCBI for BLAST software and databases
• Flask for web framework
• Pandas for data processing