Tag: multi-omics

A practical pipeline for taking personal bulk RNA-seq FASTQs through quality control, quantification, normalization, and interpretation, with the parameters and failure modes that matter when n=1.

A practical guide to choosing between untargeted and targeted metabolomics providers, what you get in the deliverable, and how to process the data yourself in mzML, XCMS, and MetaboAnalyst.

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 plasma proteomics report measures the relative abundance of hundreds to thousands of circulating proteins. Here is what the numbers mean, how the three main platforms differ, and how to analyze your own data without fooling yourself.

A working guide to taking personal proteomics data from raw instrument files or NPX tables to a quantitative matrix, QC'd and normalized, and then to within-person statistics you can defend.

A practical guide to correlating genes, samples, and timepoints in personal RNA-seq data: which transform to use before computing a coefficient, how to filter, how to handle confounders, and how to correlate expression against proteomics, labs, and continuous glucose data.

A technical assessment of the consumer blood panel companies: who runs the assays, what the $349-$499 membership buys, how to get structured data out, and why a 100-biomarker panel flags something for almost everyone.

A map of the multi-omics vendor market in four layers, what files each layer hands back, and how to evaluate a provider if you want data you can analyze yourself.

A concrete stack for working with personal genome, transcriptome, proteome, and biomarker data: file formats, tools, commands, and where each approach breaks down.