Skip to content
NEW
High-performance mixed models.
Powered by ASReml. Now in Python.
When your data is complex and your decisions matter, ASReml-Python gives you the modelling depth, statistical rigour and workflow flexibility to generate insights you can trust.
the challenge
Model the biology, not the limits of the software.
Biological data is rarely simple. Traits are connected, measurements repeat over time, and genetic and environmental effects overlap.
ASReml-Python gives you the mixed-model power to represent this complexity directly in Python. Fit demanding models without simplifying the data to fit the method. Separate genetic, biological and environmental sources of variation. Generate evidence and predictions you can trust.
When models reflect reality, decisions become more reliable.
MODELLING CAPABILITY
Go further with the models your research demands
ASReml-Python gives you the specialist mixed model capability to represent the design, relationships and variation within real research data
Complex experimental data
Preserve the structure of the experiment, without forcing difficult data into oversimplified models.
- REML linear mixed models and GLMMs
- Hierarchical and multilevel structures
- Split-plot, nested, unbalanced and incomplete data
Space and time
Account for dependence across locations and time to separate genuine effects from underlying variation.
- Spatial models and field trial analysis
- Repeated measures and longitudinal models
- Random regression
Traits and environments
Analyse connected traits and environmental responses together for a clearer view of performance.
- Multi-trait models and genetic correlations
- Multi-environment trial analysis
- Factor analytic models
Genetics and prediction
Bring known relationships into the model and generate outputs that support selection, ranking and reporting.
- Pedigree and genomic relationship matrices
- BLUEs, BLUPs and predictions
Variance and correlation structures
Model complex patterns of covariance, correlation and heterogeneity so the statistical assumptions better reflect the data.
- Flexible variance and correlation structures
- Homogeneous and heterogeneous variance models
- Residual and random-effect structures
BUILT FOR PYTHON WORKFLOWS
Put specialist mixed modelling at the heart of your Python workflow
ASReml-Python works natively within Python, bringing specialist mixed model analysis into the environment your team already uses. Prepare data, fit advanced models, explore results and continue downstream analysis without disrupting your existing workflows. The result is a more connected, reproducible and efficient way to analyse complex research data.
POWERED BY ASREML
Proven methodology, built for Python
ASReml-Python brings world-leading ASReml mixed model methodology into Python. It draws on decades of statistical development and application across biological, agricultural and genetic research.
Specialist by design
Purpose-built for demanding mixed model analysis, with the statistical depth to represent complex research data appropriately.
Decades of development
Methodology shaped by real scientific problems and continually developed for the needs of modern research.
Expert support
Backed by people who understand the software, the statistical methods and the research questions behind them.
Proven in practice
ASReml methodology has been applied to biological research around the world, supporting analysis where rigour matters.
Knowledge Base
How to use ASReml-R
Knowledge Base
How to use ASReml-Python
Download
License required for activation
Download
License required for activation
READY TO GET STARTED?
See what becomes possible when your models reflect the reality of your research
Explore ASReml-Python with your own data through a free 30-day trial, or speak to our team about the best options for your work.
Model the biology, not the limits of the software