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Aaron Mitchell-Dick

Bioinformatics you can follow.

Step-by-step walkthroughs for genomics analysis on the command line, in R, and in Python — written for the person running the pipeline for the first time, and commented with the things an experienced analyst knows and forgets to say out loud. Every command is one you can paste and run.

Start with bulk RNA-Seq About this site

Projects

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Complete3 walkthroughsBeginner
Bulk RNA-Seq: reads to differential expression
A complete bulk RNA-Seq workflow — quality control, adapter trimming, kallisto pseudoalignment, and differential expression with tximport and DESeq2.
RNA-SeqbashRDESeq2kallisto
In progress4 walkthroughsIntermediate
Single-cell RNA-Seq: from counts to cell types
Droplet-based scRNA-Seq end to end — alignment and counting, quality control that does not throw away real biology, normalisation, clustering, and annotation.
scRNA-SeqRPythonSeuratScanpy
Planned5 walkthroughsIntermediate
The statistics underneath omics
A ground-up look at the methods every omics pipeline runs on your behalf — count distributions, dispersion, normalisation, multiple testing, and what a p-value means when you computed twenty thousand of them.
StatisticsRDESeq2Methods
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Who this is for

These walkthroughs assume you have sequencing data and a biological question, and that nobody has explained what conda activate does or how your transcript IDs will match your annotation. They are written to be run start to finish, in order, on your own laptop.

If you would rather not write code at all, Galaxy is an excellent free, open-source, web-based alternative for the entire bioinformatics community.

Ground rules

Every walkthrough on this site follows the same conventions, so that once you have read one you know how to read the rest.

Convention What it means
Code blocks are shown with the shell or language they belong to bash blocks run in a terminal; r blocks run in the R console or RStudio
Output blocks appear directly under the command that produced them These are real results from a real run, not invented examples
Paths are written as placeholders path/to/your/data always means substitute your own path here
Versions are stated where they matter Where a command is version-sensitive, the version is named in the text

© 2026 Aaron Mitchell-Dick · Content CC BY 4.0, code MIT

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