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Raw counts from RNA-seq are not comparable across samples without normalization. Here is why that matters, what CPM and TPM actually do, and how to normalize in R.

A guide RNA score is only useful if your target base lands in the editing window. This post covers how to count protospacer positions, use BE-Designer for CBE and ABE guide design, manage bystander edits, and handle PAM constraints — with worked examples for both editor types.

GEO has thousands of published RNA-seq datasets — including the one from that paper you just read. This post shows you how to pull any GEO dataset into R with GEOquery, extract the count matrix and sample metadata, and save both as CSVs for downstream analysis.

A guide RNA score is only useful if you know what it measures. This post covers the sequence rules that determine Cas9 guide efficiency, how on-target scoring algorithms work and what they were trained on, off-target risk metrics, how to read CRISPOR output, and what changes when designing for Cas12a.

Six steps from raw CSV to a publication-ready figure with significance bars. A complete, copy-paste-ready R workflow using dplyr, ggplot2, and ggsignif — built on the qPCR dataset from Arc 1.