Translational dossiers, built in the same conversation as the analysis
Inflexa assembles your analysis runs into a dossier the translational team can decide on: every figure traced to its source run, every claim grounded in PubMed-cited evidence. Refine in conversation, share with a link.
Report Sections
Generated by Inflexa · Feb 21, 2026
Differential Expression
Ancestry-stratified gene expression
Your analyses are done. Brief the team.
After running differential expression, pathway enrichment, immune profiling, and survival analysis, you're sitting on results from multiple runs. One message turns them into a structured dossier.
Inflexa knows what you ran. It pulls the figures, tables, and statistics from your analysis history and assembles them into the sections a translational team expects.
One message. Every figure traced to its source run.
Completed Runs
I'll build a comprehensive report from your 5 analysis runs. Here's the structure:
Report Outline
Generating now: pulling figures from your DE, pathway, immune, TF, and survival runs...
Breast Cancer Ancestry Analysis: Report
13 sections · 23 figures · 8 tables · Click to open
The whole story on one screen
Every report opens with a structured summary: cohort size, total DEGs, key pathway hits, and immune signatures, all quantified and sourced to the underlying runs.
Top findings are ranked by effect size and statistical significance, not just listed. Reviewers see what matters first.
A 30-second read that replaces a 30-minute deep dive.
Study Overview
Key Findings
PI3K/Akt/mTOR pathway dominates African American tumors
SHAP importance 0.510 · NES = 2.34, FDR = 1.2e-06
Th2 immune infiltration elevated 2.3-fold in AA vs EA
Immune deconvolution · p = 4.1e-04
NT5E and estrogen response drive European ancestry classification
SHAP importance 0.234, 0.134 · Ancestry-stratified ML model
Significant survival divergence between ancestry groups
Log-rank p = 0.003 · AA 5-year OS: 72% vs EA: 84%
Every gene, in context
Interactive volcano plots render directly in the report. Hover any point to see the gene name, fold change, and adjusted p-value. Click to jump to the gene's full profile.
Inflexa stratifies the analysis by ancestry group, revealing gene expression patterns that are invisible in a pooled analysis. BRCA1 shows 3.2-fold upregulation in AA samples: a signal lost when cohorts are combined.
4,217 DEGs across 3 ancestry cohorts: each plotted, searchable, and linked to downstream analyses.
Outcomes that anchor the translational decision
Kaplan-Meier curves with confidence intervals, risk tables, and log-rank statistics, all generated from your survival run and rendered as interactive charts.
African American patients show significantly lower 5-year overall survival (72%) compared to European American (84%). The divergence becomes apparent after year 2, consistent with known ancestry-linked disparities in treatment access and tumor biology.
Clinical context no spreadsheet can carry: survival curves stratified by your variables of interest.
Number at Risk
| Group | 0 yr | 1 yr | 2 yr | 3 yr | 4 yr | 5 yr |
|---|---|---|---|---|---|---|
| EA | 734 | 698 | 671 | 648 | 629 | 617 |
| Arab | 24 | 23 | 21 | 20 | 19 | 19 |
| AA | 326 | 302 | 278 | 258 | 242 | 235 |
Refine it like you'd brief a colleague
Reports aren't one-shot. Rearrange sections, add context, adjust visuals, all through natural language. Every edit preserves the underlying data and statistical rigor.
Tell Inflexa what to change. It understands your analysis, so "add the immune comparison to the summary" doesn't require explaining what that means.
No re-running analyses. No exporting and re-importing. Just say what you want.
Before
1. Summary
2. Study Design
3. Cohort
4. DE
5. Pathways
6. Dose-Response
7. Immune
...
After
1. Summary ★
2. Study Design
3. Cohort
4. DE
5. Pathways
6. Immune
...
Before
After
Conclusions backed by every upstream analysis
The Synthesis section doesn't just summarize: it integrates. Each conclusion is linked to the specific analyses that support it, with confidence scored by evidence convergence.
When three independent analyses point to the same biological story, Inflexa flags it as high-confidence. When evidence is mixed, it says so.
Not a summary of summaries. A synthesis that traces every claim to its evidence chain.
PI3K/Akt/mTOR signaling is the dominant ancestry-linked pathway in AA breast cancer
Supported by differential expression (NES=2.34), SHAP feature importance (0.510), pathway enrichment (FDR=1.2e-06), and TF activity analysis showing upstream AKT1 activation. This represents a potential therapeutic target for ancestry-stratified treatment.
Immune microenvironment composition diverges significantly by ancestry
Th2 infiltration is elevated 2.3-fold in AA tumors (p=4.1e-04). This is corroborated by LAG3 expression differences (SHAP=0.290) and survival analysis showing immune-stratified outcomes.
Estrogen receptor signaling drives EA-specific tumor biology
ESR1 and FOXA1 are top SHAP features for EA classification. Estrogen response hallmark pathway is significantly enriched in EA tumors. However, this may partly reflect subtype composition differences.
Arab cohort shows intermediate molecular profile
RA-QA cohort (n=24) clusters between EA and AA on principal components. Limited sample size precludes definitive conclusions: validation with larger Arab-ancestry datasets recommended.
One link. Full context.
Share your report with a link: collaborators see the same interactive visualizations, the same evidence chains, the same conclusions. No exports, no PDFs, no lost formatting.
Anyone who needs to act on the report opens the link and gets the full picture: translational lead, biostats, clinical PI, sponsor reviewer. Every chart stays interactive. Every finding stays traceable. The context travels with the work.
Your collaborator sees exactly what you see, not a flattened copy.
Breast Cancer Ancestry Analysis
12 sections · 23 figures · 8 tables · Updated 2 min ago
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Access
Anyone with the link
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Shared with
Radu Tanasa
radu@panomics.bio
Sarah Chen
s.chen@research.edu
A catalog of sections, not a fixed template
Overview and synthesis stay consistent across every dossier. The analyses in between adapt to what you ran: a responder analysis ends with stratification rules; a target-prioritization run ends with a ranked target list; a tox readout ends with safety signals.
Summary
Key stats, top findings, study overview
Study Design
Cohorts, comparisons, methods used
Cohort Analysis
Sample demographics, group composition
Differential Expression
Volcano plots, DE tables, gene rankings
Pathways
Enrichment scores, pathway networks
Immune Profiling
Cell composition, infiltration estimates
TF Activity
Transcription factor regulation scores
Networks
Pathway interaction graphs
Genomics
Variant analysis, mutation profiles
Survival
KM curves, log-rank tests, risk tables
Synthesis
Integrated conclusions, confidence scores
Limitations
Caveats, power analysis, known gaps
See your analysis become a translational dossier
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