De novo Assembly

  • Chromosome level assemblies: Generate genome assemblies for even large polyploid genomes.
  • Polyploid genomes: Our expertise lies in assembling large, polyploid genomes up to 22 Gbp in size.
  • Genetic variance studies, marker development, and pre-breeding: We offer additional resources to apply your de novo assembly results.

Client Project: Computomics performed a de novo assembly of two indica elite rice lines using both Illumina and PacBio data. We constructed a genetic map using 2000 F2 generation individuals to build pseudochromosome level assemblies with >95% of the scaffolds in chromosomes and >99% gene space cover.

ASSEMBLY reference_based_TO_reference Kopie

De novo Annotation

  • Explore biological function: Assess isoforms and reveal biological pathways.
  • Trait mapping: Map traits to genomic positions and assess the severity of mutations in coding regions.
  • Re-annotate existing assemblies: Reveal new isoforms and non-coding RNAs.

Client Project: Using machine learning-based gene finding tools on over 40 RNASeq datasets, we annotated four reference genomes of closely related species. These tools allow us to quickly annotate your genomes from closely related species - some projects completed in just a few hours.


  • Differential gene expression: Utilize RNASeq data to discover trait-relevant regulation.
  • Combine multiple data sets: Enhance comparative analysis by combining datasets regardless of the sequencing technology.
  • Transcriptional dynamics: Explore transcriptional dynamics in plant growth and stress response.

Client Project: We compared more than 400 different RNASeq samples from seven different tissues of a polyploid crop. Using PacBio IsoSeq, we accurately determined more than 1000 novel transcript isoforms. Plant immune response genes were found to be the fastest-evolving gene family in this project.

Genotyping and Genome Graphs

  • Develop new markers: Develop thousands of new markers across the entire genome.
  • Low cost: We genotype polyploid species, even without a reference genome, at low cost.
  • Unbiased marker discovery: Get a complete overview of every part of the genome.
  • Customization: We customize the setup of your genotyping projects for each genome, species, population size for the marker amount you require.
  • Correlate traits to gene expression data: Identify traits linked to large structural variants and correlate then with gene expression data.
  • Accelerate selection: Build haplotype blocks or a genome graph to compare hundreds of varieties

Client Project: We called variants in over 400 lines of a polyploid crop and developed suitable markers for allele-specific PCR. For any project, we continuously perform all genotyping using the same, customized parameters. This makes results comparable and reproducible.

Genomic Prediction

  • Predict performance: Learn how your cross will perform before it is field-tested with our machine learning-based models.

  • High throughput: Genotype millions of genetic markers in thousands of plant lines and predict performance of millions of genotypes of potential crosses.

  • Responsive analysis design: Receive machine learning-based breeding values and phenotypes within 48 hours and improve the model with each cycle.

Client Project: We performed reference-free genotyping of four stages of a breeding program to determine which locations are most predictive for the entire region. This reduced the number of regions needed for early-stage selection from eleven to just three, freeing up space and saving costs. Our machine learning models outperformed the state-of-the-art BLUP methods by 20-40% better correlation.

Metagenomics and Microbial Genomics

  • Simultaneous visualization: Identify species, genes, transcripts, and metabolic networks simultaneously.
  • Fast and specific: Analysis of raw data of 1.8 billion reads to visualized results in only two days.
  • Explore complex communities: Investigate complex microbial communities without the need for time-consuming culturing.
  • Correlate traits to gene expression data: Identify traits linked to large structural variants and correlate then with gene expression data.

Client Project: We compared dozens of microbial samples, considering gene content, metabolic pathways, and taxonomy. The speed of our award-winning alignment tool allowed annotations using multiple reference databases. We delivered results in several formats to ensure future accessibility and immediate utility.

Learn more about the whole-genome metagenomics visualization tool - MEGAN


  • Define breeding strategies: Cutting edge methods of epigenome profiling allow you to easily define plant breeding strategies.
  • Identify new markers: Develop non-genetic markers and explore novel epialleles modulating traits
  • Identify gene expression regulators: Quickly identify regulators of gene expression and detect loci of adaptive stress responses.

Client Project: Using MethylScore, we accurately identified discrete DNA methylation differences of short-term heritability in response to hyperosmotic stress that was associated with transcriptional and phenotypic changes. We determined that these acquired adaptations were sensitively found in non-CG contexts only.