Evolution
As populations evolve so must technology. Biological evolution, be it minor or substantial, embraces change from slight differences in alleles through to successive alterations in species. At VSNi we also embrace change, continual development and new methods of analysing data in order to keep our software ahead of the game.
Why GenStat?
GenStat data analysis software is the only package of its kind to concentrate on the life sciences and provide tailored analyses for sectors within this industry. From natural selection through to genetic drift, GenStat provides the tools you need to analyse your data quickly, efficiently and more important, accurately.
- Analyse large, complex datasets easily and efficiently
- Assist in defining factors that affect your research
- Define key traits to help you discover & create new methods of productivity
- Discover patterns in vast sets of data
- Define genetic variables
- Derive parametric relationships
- Determine risk factors
- Investigate physical and biological changes
- Graphical exploration and presentation of data
- Integrate bio and climatic data
With thousands of analyses, procedures and directives a single page isn’t nearly enough to show off GenStat. The following is but a small example of some of the possibilities; to gauge the full potential why not try GenStat for yourself?
- Design experiments and plan monitoring systems
- Analysis of variance to compare species and trends
- Estimate genetic correlations using REML
- Multivariate analyses to estimate genetic correlation
- Maximise efficiency in variety evaluations
- Cluster analysis to provide similarities of species composition
- Easy data uploads to produce an array of visual data and graphics
- Partial differential equations
- Advanced modelling using HGLMs
Sciences such as biological evolution are becoming more inter-disciplinary. We understand our role is to be aware of such interactions within the sciences and provide fitting tools to help you make the most of your data.
“As an evolutionary biologist, I have learned over the years that most people do not want to see themselves as lumbering robots programmed to ensure the survival of their genes.” John Maynard Smith
