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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.
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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.- Published on
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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t.test() and aov() replace ten minutes of clicking in GraphPad Prism. Here is how to run t-tests, ANOVA, and post-hoc comparisons on your qPCR data — with code you can actually reproduce.
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ggplot2 turns your summarized qPCR data into publication-ready figures in a dozen lines of code. Here is how to build dot plots, bar charts, and multi-panel figures — and export them at 300 dpi without touching GraphPad.