Phase 4 — Single-cell RNA-seq
Module 24

scRNA-seq Concepts & Data Formats

Before writing any code, understand what makes single-cell data fundamentally different from bulk — the dropout problem, sparse matrices, AnnData and Seurat object structures, and which public datasets to use for practice.

Week 31Timeline
~7 hrsStudy time
FREEAlways
What you'll learn

Topics covered in this module

10x Genomics · droplets
Cell Ranger output
Sparse matrices
AnnData structure
Seurat object

📋 Not sure where this fits? Module 24 is part of the full bioinformatics curriculum — a structured 42-week learning path from Bash to single-cell RNA-seq.

See full curriculum →

Lessons are on their way.

We're building this module carefully — every lesson comes with exercises, datasets, and a GitHub repository you push as proof of skill. Sign up to be notified the moment it goes live.

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Module 24 of 31