Genomic Selection

High performance BLAST implementation adapted to run in Spark clusters.

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

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

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.

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

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.

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

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-quality reference genome assemblies improve Genomic Selection and breeding

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