OMICSDESKbioinformatics, delivered

You have the data.
We turn it into figures you can submit.

Analysis-only bioinformatics for single-cell, spatial and bulk transcriptomics. No sequencing contract, no minimum order — send a count matrix or an accession number and get back publication-ready results, the code that produced them, and a methods paragraph. Fixed price agreed before we start.

Proof 1

Annotation checked blind

A reference classifier run without seeing our manual labels agreed on 6/6 clusters, 100% within each. See it

Proof 2

The statistics change the answer

Pseudobulk vs per-cell on 8 donors: the two gene lists disagree on 68.3% of calls. See it

Proof 3

Integration that kept the biology

Donor clustering down 20.2%, treatment effect moved -0.1%. Measured, not asserted. See it

Open a full example report — the actual deliverable, figures embedded, methods paragraph included. Every number above was computed by a script you can download and re-run (the code is here). We publish the checks other vendors leave out — including when they are unflattering.

Five complete sample deliverables, all run on public data and fully reproducible: single-cell (2,638 cells, 6 annotated populations) · spatial (4,025 Visium spots, 10 spatial domains) · bulk RNA-seq (DESeq2, 2,414 genes up, with a biological check that passes) · pseudobulk vs per-cell (8 donors; the two methods disagree on 68.3% of calls) · differential abundance (pooling cells calls 4 cell types as changed; a donor-level test calls none) · trajectory (PAGA + pseudotime, with the branch check that most reports skip).

What we do

Single-cell RNA-seq

QC, integration, clustering, annotation, differential expression, trajectory, cell–cell communication. 10x, BD, Parse, Singleron, plate-based.

Spatial transcriptomics

Visium / Visium HD, Xenium, Stereo-seq, MERFISH: spatially variable genes, deconvolution, niche analysis, tissue overlays.

Bulk RNA-seq & more

DEG, GO/KEGG/GSEA, WGCNA, survival association; ATAC, CUT&Tag and multi-omics integration on request.

Reviewer rescue

Got a "please re-analyse" from reviewers? We reproduce, correct and extend an existing analysis, with a written response to each comment.

Reproducible handover

Every project ships containerised code and parameters. Your students can re-run it after we are gone — that is the point.

Confidential by default

NDA on request, data deleted after delivery, nothing published or reused. Unpublished data stays unpublished.

Try it on your own data before talking to anyone

Upload a count matrix and get back barcode-rank and per-cell distributions, thresholds computed from your data rather than a tutorial, the genes that dominate your counts, an expected doublet count, and a downloadable per-cell table. No account, no email, and the file is deleted when the report is built. Run it →

Guides

Practical write-ups from the same people who would do your analysis — read them before you decide anything.

The reviewer asked you to re-analyse your single-cell data. Now what?

A practical triage for the five re-analysis requests reviewers actually make, what each one really costs you in time, and how to answer without redoing the whole project.

What does single-cell RNA-seq data analysis actually cost?

Honest price ranges for scRNA-seq analysis in 2026 — in-house, core facility, freelancer and service provider — and where the hidden costs are.

scRNA-seq QC thresholds: what to actually use, and how to defend them

Why fixed cut-offs like "<5% mitochondrial" fail on some tissues, how to set data-driven thresholds, and what to report so reviewers stop asking.

→ All guides

Pricing

Indicative ranges in USD. You get a fixed written quote before any work starts — no hourly billing, no surprises.

Single-cell RNA-seq — standard analysis

$380–650
per sample · indicative

QC, filtering, normalisation, HVG, PCA/UMAP, clustering, marker genes, automated + manual cell-type annotation, publication-ready figures, methods text.

Single-cell — advanced modules

$900–3200
per project · indicative

Integration/batch correction across samples, differential abundance, pseudotime/trajectory, cell–cell communication, gene-set/pathway scoring, doublet and ambient-RNA handling.

Spatial transcriptomics analysis

$550–1400
per slide/section · indicative

Spot/cell QC, clustering, spatially variable genes, deconvolution against a reference, niche/neighbourhood analysis, overlay figures.

Bulk RNA-seq / DEG analysis

$300–900
per project · indicative

Alignment or count-matrix intake, QC, normalisation, differential expression, GO/KEGG/GSEA enrichment, volcano/heatmap figures, results tables.

Second-opinion re-analysis / reviewer response

$450–1800
per project · indicative

Independent re-run of an existing dataset, reproduction of published figures, targeted answers to reviewer comments, revised figures.

Custom pipeline / multi-omics integration

$1500–12000
quoted · indicative

Bespoke workflows, multi-omics integration, reproducible Nextflow/Snakemake delivery, containerised handover so your team can re-run everything.

Not sure what you need?

Answer four questions and get a concrete plan — the modules that fit your design, what to send, and an indicative price. It will also tell you if your design cannot support the comparison you are planning, which is worth knowing before you pay anyone. Build a plan →

Get a fixed quote

New to working with an external analyst? Here is exactly how a project runs — including what happens if your data fails QC, what we do with it afterwards, and who owns the results.

Tell us what you have. You get a scoped fixed price and a delivery date, normally within one working day.

Received — thank you.

We will come back with a fixed scope, price and delivery date, normally within one working day.