bio-de-edger-basics

Creating DGEList Object

Goal: Construct an edgeR container from a count matrix with sample group information.

Approach: Wrap raw counts and group labels into a DGEList object for normalization and testing.

"Load my RNA-seq counts into edgeR" → Create a DGEList from a count matrix with sample group assignments and optional gene annotations.

## With gene annotation

y <- DGEList(counts = counts, group = group, genes = gene_info)

## Standard edgeR Workflow (Quasi-Likelihood)

**Goal:** Run the complete edgeR QL pipeline from raw counts to differentially expressed gene lists.

**Approach:** Filter, normalize (TMM), estimate dispersions, fit quasi-likelihood GLM, and test coefficients with the QL F-test.

**"Find differentially expressed genes between my groups"** → Test for significant expression differences using negative binomial models with quasi-likelihood F-tests.

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