About
Switzerland Omics builds advanced statistical systems for genomic interpretation.
We develop software, evidence databases, and interpretation systems for precision medicine, diagnostics, pharma R&D, and clinical decision support.
Quinary inference
A fifth layer of genomics.
Genomics already has established layers for sequencing, variant calling, interpretation, and clinical use. Switzerland Omics is developing quinary inference, a fifth layer that asks how strongly the available evidence supports the complete genomic explanation.
This requires statistical models that account for observed findings, competing possibilities, missing evidence, and unresolved uncertainty. The goal is to make the strength of a genomic conclusion measurable rather than implicit.
What supports the current explanation.
Available genomic, biological, and clinical evidence contributes to the quantitative assessment.
What remains unresolved.
Plausible alternatives and missing evidence remain part of the inference rather than disappearing from the final result.
How strong the complete explanation is.
Statistical inference integrates the available evidence and remaining uncertainty into a measurable conclusion.
From methods to systems
Statistical inference needs infrastructure.
A statistical model alone is not enough. Evidence must be structured, biological knowledge represented consistently, and results kept with the context needed to review and reuse them.
We therefore build the software, evidence databases, schemas, semantics, and supporting infrastructure required to make advanced genomic inference operational.
Methods
Quantitative inference
Statistical and probabilistic methods for measuring genomic evidence, uncertainty, and competing explanations.
Systems
Software and evidence databases
Applications, databases, algorithms, and interpretation systems that bring quantitative methods into real workflows.
Infrastructure
Structure for reuse
Data semantics, schemas, evidence structures, interoperability, and governance needed to keep results usable across systems and over time.
Scientific foundation
Built on more than a decade of research.
Switzerland Omics grew from more than ten years of work across statistical genetics, multi-omics, rare disease, infection and immunity, precision medicine, and clinical data infrastructure.
This includes translational medicine at the University of Zurich and Universitäts-Kinderspital Zürich, human genomics at the Global Health Institute at EPFL, and rare disease genetics at the School of Medicine and St James’s University Hospital, University of Leeds.
The work has also involved researchers at ETH Zürich, clinics in Switzerland, Europe, and the United States, national research programmes, and partners across the biotech and pharmaceutical industries.
Switzerland Omics was founded independently, with guidance on translating science into practice from Swiss federal authorities, Innosuisse, and Venturelab.
From human genetics to quinary inference.
Our foundations span genomic discovery, statistical genetics, multi-omics, clinical research, and probabilistic interpretation.
Developed across research, clinics, biotech, and pharma.
The underlying work connects academic research, clinical programmes, university hospitals, biotechnology, and pharmaceutical settings.
Scientific methods made operational.
Our team brings training in advanced omics from the Swiss Institute of Bioinformatics, drug and device development and regulation at EPFL, and life-science venture creation through Innosuisse Venturelab.
Shared progress
Some infrastructure works better in the open.
We release selected software, methods, and technical infrastructure as open source so researchers and developers can use, test, and extend them independently.
Shared tools, schemas, and standards allow the wider ecosystem to progress in parallel with our commercial systems.
Community software
≈10K
Annual downloads across open statistical and bioinformatic tools.
Software
10+
Software releases across platforms, databases, and statistical tools, including four CRAN packages.
Shared infrastructure
3
Normative standards for reproducible genomic and statistical evidence.
