A key to providing clinical reports that deliver tangible patient benefits is the reliable and accurate detection of all the variants specific to the patient. Standard bioinformatic pipelines are effective in detecting frequently occurring variant types like SNP’s and Indels but fall short with variants such as Alu elements and mid-sized deletions.

Our bioinformatics team tirelessly develops tools that identify challenging variants, which are not addressed by best-of-breed open-source pipelines. To assist our team, we have brought together an ecosystem of experts, each familiar with a major disease and its bioinformatic challenges. This ecosystem allows us to tackle the vast majority of therapeutic and diagnostic areas.

Read our whitepaper about challenging variant detection.

Our team has developed the tools to detect the following challenging variants:

Full list of variant types

  • SNPs
  • Indel
  • Mid-sized INDEL (~150b)
  • Germline exome/WGS CNVs
  • Somatic CNVs
  • Structural Variants (SV)
  • Alu elements
  • Multi Nucleotide Variants (MNVs)
  • Anti-variants
  • Microsatellite instability (MSI)
  • RGNA Gene Fusions


detecting challenging variants in constitutional diseases SeqOne white paper miniature
White paper

Challenging variants in constitutional diseases

Challenging variants are difficult to identify but play an important role in building a complete picture of a patient. These [...]

Get whitepaper

Supporting research

A key component of our R&D strategy involves collaborating with research groups in academia and industry that contribute their expertise in specific therapeutic and diagnostic areas through collaborative research projects. As these projects progress, the resulting discoveries are often integrated into SeqOne’s bioinformatic stack, which further improves variant detection and accuracy.

If you are interested in collaborating with us on R&D projects, please contact us.

Some of our recent projects

  • Improved automated variant ranking, in collaboration with the University of Grenoble Training Hospital.
  • Use of whole genome data to improve the matching of kidney transplant donors and recipients, in collaboration with the University of Sorbonne.
  • Analysis of a large DNA / RNA pan-cancer panel to deliver therapeutic recommendations, in collaboration with the Henri Baclesse Anti-Cancer Center.

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