v2-samplesheet-parser

A lightweight Python tool to parse and validate Illumina Sample Sheet v2 format. This tool supports multiple formats including BCLConvert, Cloud, TSO500L, and TSO500S sections.

Features

• Parse CSV to JSON: Convert Illumina Sample Sheet v2 CSV format to structured JSON data
• Validate Samplesheets: Ensure samplesheets meet the required format and contain necessary sections
• Retrieve Library Information: Extract library information from samplesheets
• Revert JSON to CSV: Convert structured JSON data back to Illumina Sample Sheet v2 CSV format
• Support for multiple section types:
  • Run Info Sections (Header, Reads, Sequencing)
  • BCLConvert Sections
  • Cloud Sections
  • TSO500L Sections
  • TSO500S Sections
• Data validation using Pydantic models
• Consistent naming conventions with automatic conversion between PascalCase and snake_case
• Comprehensive error handling with detailed error messages

Installation

pip install v2-samplesheet-parser

Usage

Basic Usage

from v2_samplesheet_parser import parse_samplesheet

# Your samplesheet content as a string
samplesheet_content = """
[Header]
FileFormatVersion,2
RunName,my-illumina-sequencing-run
InstrumentPlatform,NovaSeq 6000

[Reads]
Read1Cycles,151
Read2Cycles,151
"""

# Parse the samplesheet
result = parse_samplesheet(samplesheet_content)
print(result)

Supported Section Types

The parser supports various section types:

1. Run Info Sections

   • [Header]
   • [Reads]
   • [Sequencing]

2. BCLConvert Sections

   • [BCLConvert_Settings]
   • [BCLConvert_Data]

3. Cloud Sections

   • [Cloud_Settings]
   • [Cloud_Data]

4. TSO500L Sections

   • [TSO500L_Settings]
   • [TSO500L_Data]
   • [Cloud_TSO500L_settings]
   • [Cloud_TSO500L_Data]

5. TSO500S Sections

   • [TSO500S_Settings]
   • [TSO500S_Data]
   • [Cloud_TSO500S_Settings]
   • [Cloud_TSO500S_Data]

Development

Setup Development Environment

1. Clone the repository:

git clone https://github.com/umccr/v2-samplesheet-parser.git
cd v2-samplesheet-parser

2. Install development dependencies:

pip install -e ".[dev]"

Running Tests

pytest tests/

Raising Issues

If you encounter any issues or have suggestions for improvements:

1. Check if the issue already exists in the Issue Tracker
2. If not, create a new issue with:
   • A clear description of the problem
   • Steps to reproduce
   • Expected behavior
   • Actual behavior
   • Sample data (if applicable)
   • Python version and environment details

License

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

Authors

• Ray Liu ([email protected])

Acknowledgments

• Based on the Illumina Sample Sheet v2 format specification
• Built with Pydantic for robust data validation