Distributed Computing Blast Implementation

With increasing sample numbers comes the need for automating the most valuable and most often applied protocols at Genetwister.

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

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.

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.

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

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

Advanced statistical models are needed to increase the power to discover (new) associations between genetic and phenotypic variation.

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

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

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