Distributed Computing Blast Implementation

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

Genomic selection (GS) is an alternative to marker-assisted selection, which can accelerate the genetic gain through shorter breeding cycles. Genetwister is implementing new breeding schemes and methods that integrate GS for crop improvement.

With the increasing demands for DNA molecule size and purity on the newest long read sequencing platforms, comes the need for developing new protocols for DNA isolation from different biological sources in the laboratory at Genetwister.

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

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

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

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

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.

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

CROPaware – A web based software platform for breeding and genomics data management.