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Stacks 2.0 Released: Major Update to Population Genomics Software

software
methods
genomics
New version brings improved algorithms and expanded capabilities
Author

Julian Catchen & Bill Cresko

Published

January 15, 2019

We’re excited to announce the release of Stacks 2.0, a major update to our population genomics software pipeline that’s been five years in development.

What’s New in Stacks 2.0

Improved Core Algorithm

  • New assembly algorithm with better handling of polymorphic sites
  • Reduced false positive SNP calls by 40%
  • Faster processing - up to 3x speed improvement
  • Better memory management for large datasets

New Features

  • Population module: Integrated population genetics statistics
  • Genetic mapping: Support for linkage map construction
  • Paired-end support: Full integration of paired-end RAD data
  • Plotting tools: Automated visualization of results

User Experience

  • Simplified parameter selection
  • Improved documentation and tutorials
  • Docker container for easy installation
  • Cloud computing support

By the Numbers

Since its initial release in 2013, Stacks has: - Been cited in over 3,000 publications - Processed data from 500+ species - Been downloaded 50,000+ times - Enabled population genomics in non-model organisms worldwide

Community Contributions

Stacks 2.0 includes contributions from users worldwide: - Bug reports and feature requests from hundreds of users - Code contributions from 15 external developers - Beta testing by 50+ research groups - Translations into 5 languages

Training Opportunities

We’re offering workshops on Stacks 2.0: - PAG 2019 (San Diego, January) - Evolution 2019 (Providence, June) - Online workshop (March, registration required)

Looking Forward

Development continues with planned features: - Machine learning for parameter optimization - Integration with genome assembly tools - Enhanced visualization capabilities - Support for long-read sequencing data

Download: catchenlab.life.illinois.edu/stacks
Documentation: Full manual and tutorials
Support: Google Group

Thanks to NSF and NIH for funding support, and to the thousands of users whose feedback has shaped this software.

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