4 posts
A practical, opinionated toolchain for analyzing your own genome, transcriptome, proteome, and biomarker data: which tools to use at each layer, the flags that matter, and where the failure modes are.
A practical map of omics data types, the public databases worth querying, and how to structure your own multi-omics data so annotation queries return something useful.
A practical map of the software that turns raw multi-omics files into results you can query, with the commands, formats, and failure modes that matter for a single person's data.
A concrete stack for working with personal genome, transcriptome, proteome, and biomarker data: file formats, tools, commands, and where each approach breaks down.