Cancer data, turned into biomarker evidence you can publish.
NovaGen Bioinformatics analyses TCGA and GEO cohorts, miRNA panels, qPCR runs and clinical studies for hospitals, research groups and diagnostics companies. You get validated results, journal-ready figures and code you can rerun.
Point at a highlighted miRNA to read its result.Illustrative data
We work with data from
TCGA and GDC
GEO
QuantStudio and Bio-Rad CFX
Clinical records
Surveys and questionnaires
Analysis for every stage of a biomarker study
In biomarker and clinical research, small analysis choices change the conclusion. Every project starts with quality control, so problems in the data are found before they reach your results.
Discover
Find and rank candidate biomarkers
Biomarker discovery report
Candidate biomarkers for your cancer type from TCGA and GEO: differential expression, survival and diagnostic performance, validated across independent cohorts and delivered as a ranked panel.
TCGA / GDC API
GEO
limma
DESeq2
Cox models
ROC / AUC
Gene or miRNA evidence report
Everything public data says about one target: tumour vs normal expression, stage and survival associations, and pan-cancer patterns. Useful before a grant, an assay or a partnership decision.
Pan-cancer
Clinical stage
Survival
Co-expression
Machine learning biomarker models
Diagnostic and prognostic classifiers from expression or clinical data, with feature selection, cross-validation and honest performance reporting.
LASSO
Random forest
Logistic regression
Cross-validation
Analyse
Turn your study data into results
qPCR and miRNA panel analysis
ΔΔCt and efficiency-corrected quantification, reference gene selection, hemolysis and spike-in checks, statistics and publication figures.
2−ΔΔCt
geNorm
Global mean
Hemolysis QC
Clinical and survey statistics
Statistical analysis for clinical studies and knowledge, attitude and practice surveys, delivered as journal-format tables with a full record of every test.
Regression
Survival analysis
Reliability
Sample size
Pathway and enrichment analysis
What your gene or miRNA list means biologically: target prediction, gene ontology and pathway enrichment, presented as clear tables and figures.
GO
KEGG
Reactome
GSEA
Target prediction
Publish and build
Figures, apps and pipelines that last
Publication-ready figures
Your results turned into clean, journal-format figures: volcano plots, heatmaps, survival curves, ROC curves and forest plots.
300 dpi PNG
SVG
PDF
Journal sizing
Custom analysis apps
A private web app built around your lab's workflow, so everyone runs the same validated analysis on every new dataset.
Python
Streamlit
Automated tests
Reproducible pipelines
Scattered scripts and spreadsheets turned into documented, version-controlled pipelines that give the same answer every time.
Python
Google Colab
GitHub
See what a report contains
Three of the figures a typical biomarker report includes, drawn here from illustrative data. Your report carries the statistics behind each one and the code that made it.
Illustrative data, 240 patients.
Does the marker predict survival?
What it shows
Overall survival for patients with high and low expression, with censored patients marked and the hazard ratio from a Cox model.
In your report
Univariate and multivariate Cox tables adjusted for stage and age, cut-off method, and numbers at risk.
Illustrative data, tumour vs normal.
Can it tell tumour from normal?
What it shows
How well a single marker and a combined panel separate the two groups, summarised as the area under the curve.
In your report
AUC with 95% confidence intervals, sensitivity and specificity at the chosen cut-off, and validation in an independent cohort.
Illustrative data, mean ± SD, n = 12 per group.
Did expression change in your samples?
What it shows
Log2 fold change for each target after normalisation, with error bars and significance from the appropriate test.
In your report
Reference gene stability, sample quality flags, the full ΔCt table and the statistical test used for each target.
Built for research teams
We work remotely with teams in Saudi Arabia, the Gulf and worldwide, with a clear scope and a fixed price agreed in writing.
Hospitals and research centres
Clinical and genomic data analysed by a dedicated analyst, without hiring an in-house statistician.
University research groups
Faculty, residents and graduate students with data waiting to become a paper, thesis or grant.
Diagnostics and biotech companies
Biomarker candidates and proof-of-concept evidence from public cancer data, ready for partners and investors.
Per project
Fixed-price analysis
One study, one agreed scope. You receive an analysis plan and a fixed quote before any work starts.
For a single paper, thesis chapter or report
Monthly
Research analytics support
A set number of analysis hours each month for your department or group, with priority turnaround and one analyst who knows your data.
For teams with a steady flow of studies
Free tools for researchers
Open-source apps for analysis problems we see again and again. Free to use, validated against independent calculations, with the code on GitHub.
miRNA qPCR Analyzer
For QuantStudio and Bio-Rad CFX exports
Upload your instrument export as it is. The app checks sample quality before it calculates anything, then gives fold changes, statistics and a publication-ready figure.
Hemolysis check for serum and plasma (miR-23a / miR-451a)
Spike-in recovery to catch failed extractions
Reference gene, spike-in or global mean normalisation
44 automated tests against independent calculations
Upload a raw questionnaire export from CSV or Excel. The app scores each domain, runs the statistics journals expect and writes a Word report with three-line tables.
Answer-key scoring, Likert mapping and Bloom's cut-offs
KR-20 and Cronbach's α reliability with confidence intervals
Chi-square, group comparisons and logistic regression with adjusted odds ratios