Association analysis

Genomic selection (GS) accelerates achieving genetic gain through shorter breeding cycles and is an alternative to marker-assisted selection. Genetwister implements new breeding schemes and methods that integrate GS for crop improvement.

At Genetwister, tools are developed using distributed computing models and technologies like Spark and Hadoop.

Tailored marker selection allowing for genotyping regardless of species, genome size and ploidy level.

Genetwister investigates new precision phenotyping methods to integrate phenotypic data into genetic models to support breeding

Discovery of markers in all plant species by next-generation sequencing for accelerated plant breeding

Acceleration and cost reduction in plant breeding with improved genotype/phenotype relations, utilizing linked variants.

Appropriate experimental design and data analysis of breeding trials are essential. Genetwister offers assistance in the experimental design, taking into account all practical considerations of the breeding program.

High performance BLAST implementation adapted to run in Spark clusters.

With increasing sample numbers and marker panel sizes, it is valuable to increase the throughput of sequencing and genotyping procedures. Genetwister develops cost-effective methods and applies available methods for allowing high-throughput genomics.

To interconnect different knowledge domains, we use different semantic web technologies.