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  • Understanding RNA-seq data: what those count matrices actually mean
    Published on
    May 5, 2026

    Understanding RNA-seq data: what those count matrices actually mean

    explainerRbioinformaticsr-seriesrna-seqbeginner
    Before you run DESeq2, you need to understand what those numbers in your count matrix actually represent. This post explains what RNA-seq count data is, why raw counts are misleading, and exactly what format DESeq2 expects.
  • T7E1 and Surveyor assays: how they work, their limits, and how to interpret results
    Published on
    April 30, 2026

    T7E1 and Surveyor assays: how they work, their limits, and how to interpret results

    crispr-seriescrisprgene-editingbeginnerhow-to
    Mismatch-cleavage assays are the quickest and cheapest way to see if your CRISPR edit actually worked. This guide breaks down the mechanism of T7E1 and Surveyor nucleases, why the "denature and re-anneal" step is critical, and how to turn gel bands into an editing percentage.
  • What is Bioconductor, and why does everyone in bioinformatics use it?
    Published on
    April 21, 2026

    What is Bioconductor, and why does everyone in bioinformatics use it?

    explainerRbioinformaticsr-seriesbeginner
    If R is a smart phone, Bioconductor is the App Store for biology. This post explains why bioinformatics has its own package repository, why it’s better than CRAN for scientists, and how to keep your biological analysis reproducible.
  • How to download public gene expression datasets from GEO in R
    Published on
    March 24, 2026

    How to download public gene expression datasets from GEO in R

    r-seriesRbioinformaticsbeginner
    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.
  • From raw data to final figure: a complete R workflow for bench biologists
    Published on
    March 17, 2026

    From raw data to final figure: a complete R workflow for bench biologists

    how-toRbioinformaticsbeginnerr-series
    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.
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