Where wet lab meets dry lab

A Harvard structural biology lab just open-sourced the software it runs its own bench on — notebook, registry, cryo-EM grid tracking, and an AI agent, all self-hosted under AGPL. I installed it and ran it. Here is what actually works, and what you should know before trusting it with your lab records.

Your DESeq2 results table has thousands of rows, and sorting it in Excel tells you almost nothing about your experiment. Here is how to build volcano plots and MA plots in R with ggplot2 — and how to read what they are actually telling you.

Short-read amplicon NGS is the gold standard for CRISPR indel detection — but it has a blind spot for structural variants, large deletions, and complex rearrangements. Long-read sequencing from Oxford Nanopore or PacBio fills that gap. Here is when it matters and how to actually run the analysis.

You can run a Western blot but you are terrified of the terminal. Here is everything a bench biologist actually needs to know about the command line — navigating files, counting sequences, searching data, and writing one-liners that replace an hour of Excel work.

You installed samtools and it broke your entire Python setup. Or DESeq2 needs R 4.3 but your system has R 4.1. Here is how Conda solves the dependency nightmare that every biologist runs into — with real commands, real installs, and real output.