Tiny

Tiny is a powerful terminal-based bioinformatics tool designed for DNA sequence analysis. It provides various features for analyzing, comparing, and discovering patterns in DNA sequences from any organism, including bacterial, fungal, viral, plant, and animal genomes.

Features

1. Basic DNA Analysis

• Sequence validation with IUPAC ambiguous base support
• GC content calculation (handles ambiguous bases)
• Molecular weight calculation
• Base composition analysis
• Complement and reverse complement sequences

2. Sequence Comparison

• Pairwise sequence alignment
  • Global alignment (Needleman-Wunsch algorithm)
  • Local alignment (Smith-Waterman algorithm)
  • Semi-global alignment
• Mutation detection
• Sequence identity calculation
• Gap analysis

3. Motif Finding

• Variable-length motif detection
• Frequency analysis
• Position tracking
• Consensus score calculation
• Custom minimum frequency thresholds

4. Regulatory Element Analysis

• TATA box detection
• GC box detection
• CAAT box detection
• Palindromic sequence identification
• Position information for all elements

5. Enhanced Feature Analysis

• Comprehensive feature overview for GenBank files
• Feature type filtering and counting
• Customizable feature display limits
• Detailed qualifier information
• JSON export for complete feature data

6. File Format Support

• FASTA (.fa, .fasta)
• FASTQ (.fq, .fastq)
• GenBank (.gb, .gbk, .genbank)
• EMBL (.embl)
• JSON output format

7. Enhanced Visualization

• Progress bars for long operations
• Color-coded output
• Formatted tables
• Summary statistics
• Clear section separators

8. Feature Analysis Options

• --feature-limit: Control number of features displayed (0 for all)
• --feature-type: Filter specific feature types(CDS, gene, tRNA, etc.)
• --save-features: Export complete feature data to JSON
• --format-info: Show detailed format-specific information

Installation 📦

Prerequisites

• Python 3.12+ (tested on 3.12, 3.13, 3.14)
• Poetry 2.x (Python package manager)

For detailed install / run / troubleshooting steps see INSTRUCTIONS.md.

Quick start

git clone https://github.com/Bjorn99/Tiny.git
cd Tiny
poetry install                 # core install (no SAM/BAM support)
poetry install --extras sam    # add pysam for SAM/BAM (Python 3.12/3.13 only)
poetry run tiny --version
poetry run tiny analyze ATCGATCG

To work inside the venv (Poetry 2.x):

# Poetry prints the activation command; run it. Fish example:
source (poetry env info --path)/bin/activate.fish
# Or bash/zsh:
source "$(poetry env info --path)/bin/activate"

Usage

For a comprehensive list of examples and use cases, check out the Examples.md. For install and troubleshooting see INSTRUCTIONS.md.

Version and help

tiny --version           # print version (e.g. tiny 0.2.0)
tiny --help              # global help
tiny analyze --help      # per-command help
tiny supported-formats   # list supported file formats

Basic Analysis

# Analyze single or multiple sequences
tiny analyze ATCG GCTA

# Analyze sequences from files
tiny analyze --input sequence.fasta
tiny analyze --input sequence.gb --format-info

# Control feature display
tiny analyze --input sequence.gb --format-info --feature-limit 10
tiny analyze --input sequence.gb --format-info --feature-type CDS
tiny analyze --input sequence.gb --format-info --save-features

# Save analysis results to a file
tiny analyze ATCG GCTA --output results.json

Sequence Alignment

# Global alignment
tiny align ATCGATCG ATCTATCG --mode global

# Local alignment
tiny align ATCGATCG ATCTATCG --mode local

# Semi-global alignment
tiny align ATCGATCG ATCTATCG --mode semi-global

Motif Finding

# Find motifs of length 4 that appear at least twice
tiny find-motifs ATCGATCG ATCTATCG ATCGAGCG --length 4 --min-freq 2

# Find motifs in sequences from a file
tiny find-motifs --input sequences.fasta --length 6 --min-freq 3

Regulatory Element Analysis

# Find regulatory elements in a sequence
tiny find-regulatory TATAAAAGGCGGGCCAATATCGATCG

Limitations and Considerations ⚠️

1. Performance Limitations

   • Designed for targeted-panel scale, not whole-genome data
   • Memory usage increases significantly with sequence length in pairwise alignments
   • Motif finding can be computationally intensive for long sequences

2. Input Capabilities

   • DNA sequences with full IUPAC ambiguous-base support
   • RNA sequences via RNASequence class (programmatic API; CLI exposure planned)
   • Supports multiple file formats (FASTA, FASTQ, GenBank, EMBL, plus SAM/BAM with the sam extra)
   • Hard cap on per-sequence length: 10,000 bp (raises ResourceLimitError). Override per-call with TINY_MAX_SEQUENCE=50000 tiny analyze ....

3. Analysis Limitations

   • No support for multiple sequence alignment
   • No secondary structure prediction
   • No phylogenetic analysis capabilities
   • No support for genome-scale analyses

Tips for using the tool effectively:

• Validate your input sequences before analysis
• Use appropriate alignment modes based on your sequences
• Consider sequence length limitations (max 10,000 bp)
• Use format-specific information with --format-info flag
• Save results to files for later analysis
• Use file input for multiple sequence analysis

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License 📄

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

Acknowledgments

• Built with BioPython
• Project and dependency management with Poetry
• CLI interface powered by Typer
• Terminal formatting by Rich

Project Status

Tiny is under active revival (Phase 0 complete: foundation hardening — typed errors, lazy heavy deps, CI, RNA class, version flag, resource limits). Future planned features:

• CLI exposure for RNA sequence analysis
• Multiple sequence alignment
• Phylogenetic analysis
• Secondary structure prediction
• Support for additional file formats
• Performance optimizations for longer sequences
• Advanced statistical analysis
• Integration with external databases

Support

If you encounter any issues or have questions, please:

1. Check the existing issues on GitHub
2. Create a new issue if your problem isn't already reported
3. Provide as much detail as possible about your problem

References

This tool implements methods and algorithms from various scientific publications. For a complete list of references, see REFERENCES.md. Key references include:

• Needleman-Wunsch algorithm: Needleman & Wunsch (1970), Journal of Molecular Biology
• Smith-Waterman algorithm: Smith & Waterman (1981), Journal of Molecular Biology
• IUPAC ambiguous base notation: Cornish-Bowden (1985), Nucleic Acids Research
• Motif finding methods: Bailey & Elkan (1994), ISMB Proceedings
• Regulatory element analysis: Bucher (1990), Journal of Molecular Biology

The tool is built using BioPython (Cock et al., 2009) and other open-source libraries. For implementation details and additional references, please refer to the full references list.