GENE-LEVEL EXPRESSION
How much?
Measures changes in the total expression associated with a gene.
OUR TECHNOLOGY
Change the resolution.
Refine the question.
A transcript-level view adds detail to the gene-level picture. Our approach connects analytical layers while keeping their limitations visible.
TRANSCRIPT USAGE
Which proportions?
Examines changes in the relative use of the gene’s transcript isoforms.
Illustrative synthetic example; not derived from client or patient data. Numbers show arbitrary total abundance and example percentage proportions.
EVIDENCE IN CONTEXT
Each layer answers
a different question.
No single analytical result tells the whole biological story.
Quality before interpretation
Read quality and study design shape what can be inferred. Eligibility and quality review are part of the analysis.
Statistical assessment
DRIMSeq and stageR support differential usage testing and stage-wise error control. Statistical evidence is interpreted within the study’s design and assumptions.
Structural corroboration
Transcript structures and applicable junction evidence help contextualize candidate shifts. Short-read evidence has limits and does not automatically establish full-length isoform structure.
Functional interpretation
Selected annotations and protein consequence characterization support hypotheses for further study; they do not prove a biological mechanism.
FOCUSED BY DESIGN
Clear methods.
Defined boundaries.
Our current commercial service focuses on annotated human transcripts in eligible bulk RNA-seq studies. Novel splicing discovery is a separate capability under qualification.
We communicate the agreed analytical scope, representative outputs, and interpretation limits before work begins.
Review the available service →START A CONVERSATION
A different view of your RNA-seq data.
Tell us about your research question. We’ll help assess whether transcript usage analysis fits your study.