Software Development

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

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

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.

Using state-of-the-art long read sequencing technologies, Genetwister builds high quality genome assemblies of novel species and obtains long-range genomic information such as haplotypes and structural variants.

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

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

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.

High performance BLAST implementation adapted to run in Spark clusters.

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

High-quality reference genome assemblies improve Genomic Selection and breeding