Hands-on Labs

Practical exercises for the RNA-seq Data Analysis Course

Lab Overview

Lab 1 · Module 2

Genomic File Formats

Explore common RNA-seq file formats: FASTQ, FASTA, GTF/GFF, BAM/SAM, BED, VCF. Understand header structures, quality encoding, and how each format is used in the analysis pipeline.

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Lab 2 · Module 2

Public Data Retrieval

Retrieve the GRCh38 reference genome and GTF annotation using NCBI datasets. Download GSE136366 FASTQ files via sra-toolkit and subsample to 1M reads using seqkit.

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Lab 3 · Module 3

QC, Trimming & MultiQC

Assess raw read quality with FastQC, trim adapters and low-quality bases with fastp, and aggregate reports across all GSE136366 samples using MultiQC.

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Lab 4 · Module 4

Read Alignment with STAR

Build a STAR genome index (GRCh38 + Ensembl GTF), align subsampled GSE136366 reads, index BAM with samtools, mark duplicates with Picard, and visualize alignments in IGV.

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Lab 5 · Module 5

Salmon Quantification & Exploratory Analysis

Build a Salmon transcript index, quantify all GSE136366 samples with GC-bias correction, import counts into R with tximport, and perform PCA and sample-distance heatmap.

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Lab 6 · Module 6

nf-core/rnaseq Workflow

Write a samplesheet for GSE136366, launch nf-core/rnaseq (STAR + Salmon) on Ibex with Singularity and SLURM, monitor progress, and explore the MultiQC report and merged count matrix.

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Lab 7 · Module 7

Differential Expression with DESeq2

Load Salmon counts via tximport, build a DESeqDataSet, run DESeq2 for KO vs control, apply apeglm LFC shrinkage, and produce volcano plots, MA plots, and a heatmap of top 50 DE genes.

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Lab 8 · Module 8

Functional Enrichment & GSEA

Run GO (BP) and KEGG enrichment with clusterProfiler on DE genes from GSE136366. Perform GSEA using fgsea with MSigDB Hallmarks. Produce dotplots and enrichment plots.

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Lab 9 · Module 9

nf-core/differentialabundance

Prepare samplesheet and contrasts CSV for GSE136366, run nf-core/differentialabundance on Ibex, and interpret the automated DESeq2 results, MultiQC dashboard, and interactive Shiny app.

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Lab 10 · Module 10

Real-world Analysis Capstone

End-to-end independent analysis: download data, run QC, align, quantify, perform DEA with DESeq2, run functional enrichment, and optionally execute both nf-core workflows on GSE136366 or your own dataset.

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