Power your decision-making

A statistical genetics pipeline to help breeders make decisions
  • A wide variety of experimental designs that allow precise estimation of genotypic effects and contrasts while correcting for noise factors.
  • Quantitative genetic analyses for all types of breeding populations that deliver estimates for important statistical genetic parameters such as repeatabilities, heritabilities, and genetic and environmental variances, covariances, and correlations.
  • Exploration and quantification of genetic diversity and distances using sequence, molecular marker and phenotypic data. Preparation for genotype-to-phenotype modelling.
  • To locate quantitative trait loci on chromosomes, a powerful map construction algorithm is available that efficiently produces genetic maps for biparental and multiparental populations.
  • Extensive suite of methods and visualizations to deal with the major problem in plant breeding and evolutionary biology: genotype by environment interaction, where genotypic differences are conditional on the environment, and achieving the breeders’ main objective, selection of the best genotypes, becomes complicated.
  • A powerful mixed model based approach identifies quantitative trait loci (QTLs) for whichever kind of breeding population, mating type, ploidy level, number of traits and environments.
  • Data fusion and integration of high throughput genotyping, phenotyping and omics data.
  • Decision support for selection of superior genotypes and crossing partners.
  • Visualization tools to support reporting and decision making.
A statistical genetics pipeline for innovation and integration
  • Designed to allow smooth information exchange of data between the statistical algorithms, visualization tools, databases and applications
  • Problem solving across large collections of high dimensional data • (genomic and phenotypic)
  • The statistical genetic pipeline API provides a standard interface to access the tools and algorithms to serve analysis to their applications
  • The pipeline embeds new algorithms and methods for spatial analysis of field trials by two-dimensional splines.
  • The generation of conditional QTL genotype probabilities for all kinds of breeding populations by a continuous time Markov process, used in genetic map construction and QTL mapping, and mixed model estimation algorithms for multi-trait analysis.
  • The pipeline is based on R procedures that call on asreml-R mixed model procedures.
  • The pipeline makes state of the art statistical and decision support methods accessible to a wide audience of breeders and geneticists via an intuitive user interfaces. The modularity of the pipeline allows easy adaptation to specific user requirements.