OMICSDESKbioinformatics, delivered

Guides

Written for people who have the data and have to make decisions about it. No sign-up, nothing gated.

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.

Cell type annotation: manual markers, automated references, or both?

How to annotate single-cell clusters so the labels survive peer review — the failure modes of each approach and a workflow that combines them.

Outsourcing bioinformatics analysis: a checklist before you pay anyone

Twelve questions that separate a deliverable you can publish from a folder of plots — data handling, reproducibility, revisions, and who owns what.

Spatial transcriptomics analysis, explained without the marketing

What deconvolution, spatially variable genes and niche analysis actually do, which platform needs which method, and where spatial analyses usually go wrong.

Pseudobulk or per-cell? The differential expression choice that decides whether your paper survives

Why per-cell differential expression inflates false positives, when pseudobulk is the right answer, and exactly how to run it.

Re-using public single-cell data without inheriting someone else’s mistakes

A practical route from a GEO accession to an analysis you can trust — what to check in the metadata, when raw counts matter, and the traps in combining datasets.

How to hand your sequencing data to an analyst (and get a better result back)

The file formats, metadata and written questions that turn a two-week analysis into a three-day one — with a copy-paste checklist.

Visium, Xenium or Stereo-seq: choosing a spatial platform before you spend the money

What each spatial technology actually measures, what resolution really means in practice, and which question each one can and cannot answer.

Doublets and ambient RNA: the two artefacts that invent cell types

How to tell a real rare population from a doublet cluster or ambient contamination, which tools to use, and the order to run them in.

Batch integration: Harmony, scVI, CCA and the failure nobody plots

How to choose an integration method, how to tell over-correction from correction, and the checks that show your biology survived.

Cell–cell communication analysis: what CellChat and CellPhoneDB can honestly tell you

Ligand–receptor scoring is a hypothesis generator, not evidence of interaction. How to run it defensibly and how to report it.

How long does single-cell analysis take, realistically?

Timelines for each stage of a single-cell project, what actually causes delays, and how to compress a deadline without cutting corners.

Cell Ranger output explained: which files matter, and which you can ignore

A file-by-file walkthrough of the 10x Cell Ranger output directory — what each one is for, which to keep, and which to send when someone asks for your data.

Budgeting bioinformatics in a grant application

What to put in the budget for analysis, how to justify it to a review panel, and the line items applicants forget until the money is already allocated.