TraitSeq covers the entire analytical journey, from preprocessing, multi-method analysis, and AI-driven mechanistic interpretation, across all major omics types.
Every TraitSeq analysis applies the complete suite of methods to your data, across transcriptomics, metabolomics, and multi-omics, run in parallel, integrated across results, not siloed. The breadth is what makes the interpretation possible.
Before any differential analysis, the platform maps your experiment’s global structure: which factors explain the most variance, whether samples cluster as expected, and where outliers sit. Data preprocessing, quality control, normalisation, and batch correction are all handled automatically.
Robust differential expression analysis with adaptive shrinkage for denoised effect sizes. Multi-factor designs, dose-response trends, interaction effects, and transcript-level isoform analysis, not just pairwise gene comparisons.
Enrichment analysis with extensive biological annotation across transcription factors, hormone signalling, stress response pathways, protein domains, enzyme classes, and more. This breadth reveals biology insights that narrower analyses miss.
Co-expression networks reveal groups of genes that respond together, often mapping to biological processes invisible in single-gene analysis. Regulatory network inference identifies which transcription factors are driving the response.
Every significant gene is individually researched against the species knowledge graph to the same depth shown below. Select a gene to see how characterisation reveals its role, its relationship to other findings, and its contribution to answering the research question.
Showing 5 key genes of the thousands characterised in this analysis
The mechanistic report synthesises findings from every analysis into an evidence-attributed narrative: executive summary, mechanistic model, biomarker panels, and actionable recommendations. Every claim links to the data that produced it. Publication-ready and designed to be handed directly to your board, regulatory team, or development programme.
Bring biological evidence to your decision making across the full development cycle: from early screening, through R&D, regulatory, product positioning, marketing, and customer use. Your product, your questions, your data, your insights.