A constantly increasing number of samples requires the throughput in the lab to be scaled up accordingly. At Genetwister, we program our state-of-the-art liquid handler to process large numbers of samples to be efficiently prepared for sequencing.
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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.
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-quality reference genome assemblies improve Genomic Selection and breeding
High performance BLAST implementation adapted to run in Spark clusters.
CROPaware – A web based software platform for breeding and genomics data management.
Leafy - Our state-of-the-art lead dicovery platform.
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.
Discovery of markers in all plant species by next-generation sequencing for accelerated plant breeding
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.
At Genetwister, tools are developed using distributed computing models and technologies like Spark and Hadoop.