Unveiling extensive variation within the somatic genome
Using the most accurate and sensitive sequencing technology in the world, Quotient’s platform reveals a new universe of somatic genome variation, uncovering novel links between genes and disease and revealing a path to create transformative therapeutics with naturally selected targets.
This first ever Somatic Genomics platform uses four key steps to study human natural target selection: phenotyping, isolation, genotyping and computation.
Phenotype cells from diseased human tissue
Using clinical samples, diseased tissue is deeply phenotyped to identify cells that are showing disease pathology and those that appear healthy.
Isolate cells of interest
Cells are isolated for sequencing, enriching for the right cell types and for phenotypes of interest.
Genotype mutations at unprecedented resolution
Single-molecule genotyping identifies somatic mutations that drive a phenotype with high confidence, demonstrating a 10 million-fold better error rate than standard approaches.
Compute the most promising drug targets
With the first comprehensive somatic genomics dataset, naturally selected genes, proteins and pathways are identified through proprietary computation pipelines for the development of transformative therapies to cure, prevent or reverse disease.
Somatic Genomics is the next revolution in genetics with key advantages to identify novel targets and better understand health and disease.
Disease biology naturally selects for key somatic phenotypes that can be linked to specific genes. Our Somatic Genomics platform can identify a broad scope of genes undetected by traditional population genetics approaches using fewer patients. This detailed resolution enables unprecedented insight and the ability to create truly transformative therapies.
Learn more about the science of Somatic Genomics
NatureMay 20, 2021Somatic Mutation Landscapes at Single-Molecule ResolutionFederico Abascal et al.
CellNovember 2017Universal Patterns of Selection in Cancer and Somatic TissuesIñigo Martincorena et al.