RESEARCH PROBLEM

How can a research team inspect differential-expression results without losing statistical and biological context?

Use an evidence-aware visual workflow that keeps effect size, adjusted significance, expression patterns and study design visible together.

WHY THIS IS DIFFICULT

Long DEG tables hide coordinated patterns

Thresholds are easily mistaken for biological boundaries

Figures can become detached from upstream assumptions

RESPONSIBLE APPROACH

1

Validate required fields and comparison labels

2

Inspect volcano, heatmap and sample-level views together

3

Record thresholds and provenance with exported figures

RELEVANT FORNEUS RESEARCH

Working demonstration

OmicsVis — Differential Expression Explorer

Interactive exploration of differential gene expression and transcriptomic result tables.

View evidence and screenshots ↗
Working demonstration

GEO Data Miner & GSEA

A guided workflow for finding public GEO studies and preparing differential-expression and enrichment analysis.

View evidence and screenshots ↗

INTERPRETATION BOUNDARY

  • The workflow does not replace raw-read processing
  • Results remain dependent on experimental design and upstream statistics

QUESTIONS THIS PAGE ANSWERS

  • interactive DEG visualisation
  • how to interpret a volcano plot
  • explore transcriptomics biomarkers