Bulk RNA-Seq analysis

Quantification, differential expression and pathway enrichment. Your data analysed, interpreted and delivered as a complete interactive report, not a raw gene list. Biology you can act on, whether the next step is a publication or an R&D decision.

72hTypical turnaround for a standard design
AuditableReproducible, versioned Snakemake pipeline
DE GenesPublication-ready annotated tables and figures
Request a quote See what you get

Confidential discussion under NDA · response within 48 hours

Interactive bulk RNA-seq report: volcano plot, MA plot and heatmap of differentially expressed genes

Why it matters

A spreadsheet of 20,000 genes is not a result

Most RNA-seq projects stall at the same point: a raw count matrix and a list of thousands of genes that no one has time to interpret. We take your sequencing data the rest of the way, with rigorous statistics, the right contrasts, and results placed in their biological context. The point is to reach conclusions: a figure for your paper, a target to prioritise, a clear go / no-go for your programme. Not more files.

Analytical pipeline

A transparent, end-to-end workflow

Every stage uses field-standard, peer-reviewed tools, with parameters justified by your data, never arbitrary defaults.

FASTQ

Raw reads or count matrix

QC & Trimming

fastp · Q30 · per-sample stats

Quantification

Salmon or STAR alignment

Differential expression

DESeq2 · robust modelling

Enrichment

GSEA / ORA · Hallmarks, GO, KEGG

HTML report

Interactive · self-contained

The deliverable

An interactive report, immediately actionable

Every analysis ships with a self-contained HTML dashboard: no installation, no licence, and it works in any browser. Your key results are visible in seconds and ready to share with your team or steering committee.

RNA-seq report: quality control summary with mapping rates and Q30 per sample
QC & mappingRead quality, trimming and alignment rates at a glance.
RNA-seq report: differential expression volcano plot, MA plot and heatmap
Differential expressionVolcano, MA plot, heatmaps and per-gene stripplots.
RNA-seq report: interactive, sortable table of top differentially expressed genes
Top DEGsInteractive, filterable table sorted by adjusted p-value.
RNA-seq report: gene set enrichment analysis dotplots for Hallmarks and GO
Pathway enrichmentGSEA & ORA across Hallmarks, GO, KEGG and Reactome.

Instant

Key results visible in seconds. No software to install, nothing to configure: just open the file.

Shareable

A single HTML file to forward to a collaborator, PI or steering committee, with everything embedded.

Traceable

Tool versions, parameters and genome references documented, with a SHA-256 manifest for every output.

What's inside the report

  • QC & trimmingRead quality, Q30, fastp stats per sample.
  • Quantification & alignmentMapping rate per sample, Salmon or STAR.
  • Differential expressionVolcano · MA plot · heatmap · stripplots.
  • PCA & clusteringGroup structure and outlier detection.
  • Top DEGsInteractive table sorted by adjusted p-value.
  • GSEA / ORA (option)Hallmarks, GO-BP, KEGG, Reactome.
  • Run infoTool versions, references, parameters.

Delivery formats

  • Self-contained HTML report: everything embedded, opens offline.
  • High-resolution PDF figures: publication-ready.
  • Annotated TSV tables: official gene symbols (HGNC).
  • DESeq2 .rds object: for your own reuse.
  • SHA-256 manifest: integrity for every file.

How we work

Rigour you can defend to a reviewer or an R&D committee

Data-driven thresholds

Filtering and cut-offs are justified by the actual distribution of your data, not copy-pasted defaults.

Versioned pipeline

A Snakemake workflow with pinned tool versions means the same input always yields the same result.

Readable annotation

Gene identifiers mapped to official symbols, so your tables are usable by biologists, not just by machines.

Biological interpretation

Results are placed in functional context, turning a gene list into an interpretable signature.

Getting started

Data we accept

Whatever stage you are at, we can pick up your project, from the sequencer's raw output to a matrix you have already generated.

Raw sequencing reads

  • FASTQ files, paired-end or single-end
  • Gzipped (.fastq.gz)
  • Any sequencing depth and read length

Pre-existing count matrix

  • counts.tsv / CSV matrices
  • featureCounts or HTSeq output
  • We start straight at the statistics

Any organism

  • Human, mouse, rat as standard
  • Non-model species supported
  • Custom reference genome / annotation

Frequently asked questions

Do you start from FASTQ files or a count matrix?

Both. We can process raw FASTQ files (paired- or single-end, gzipped) through our full pipeline, or start from an existing count matrix (counts.tsv, featureCounts, HTSeq) if alignment has already been performed.

How many samples and replicates do I need?

At least three biological replicates per condition is recommended for robust differential expression. Fewer replicates are possible for exploratory work, and we are happy to advise on statistical power before you sequence.

Which organisms do you support?

Any species with a reference genome or transcriptome: human, mouse and rat as standard, as well as non-model organisms. Gene identifiers are mapped to official symbols (HGNC for human) for readable, publication-ready tables.

What is the typical turnaround time?

A standard design (for example two conditions with replicates) is typically delivered within 72 hours of receiving your data. More complex designs take longer, and we confirm a precise timeline before starting.

Can you handle complex experimental designs?

Yes. Multiple factors, batch effects, paired samples and time-course designs are modelled explicitly in DESeq2, so that the differential expression results reflect your real experimental structure rather than a simplified two-group comparison.

How is my data kept confidential?

We sign a non-disclosure agreement before any data transfer, exchange data through secure channels and never share or reuse your data. Where your institution has specific security requirements, we comply with them fully.

What if I need analyses beyond the standard report?

The standard report is a starting point. We routinely add custom figures, additional contrasts, gene-set signatures of interest or bespoke downstream analyses, and can integrate the results with other omics layers when needed.

How much does a bulk RNA-seq analysis cost?

The cost depends on three factors: the experimental design (number of conditions and contrasts), the number of samples, and the depth of analysis requested. A straightforward two-group comparison with a standard interactive report typically starts below €1,500. More complex designs, additional pathway databases or custom downstream analyses are scoped and quoted transparently before any work begins. Contact us with your design and we will send a flat-rate quote within 48 hours.

Ready to turn your RNA-seq data into results?

Send us your design and data type, and we'll reply with a clear scope, timeline and transparent flat-rate quote.

Confidential discussion under NDA. Response within 48 hours.

Request a quote