Course Schedule

RNA-seq Data Analysis Course — 5–9 April 2026 • KAUST, Thuwal

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Day 1 — Sun 5 Apr Day 2 — Mon 6 Apr Day 3 — Tue 7 Apr Day 4 — Wed 8 Apr Day 5 — Thu 9 Apr

Day 1 — Sunday, 5 April 2026

Module 1: Biological Background

Time Type Topic Tools / Resources Instructor
09:00 – 09:15 Welcome Course introduction, logistics, and learning objectives — Husen Umer
09:15 – 10:00 Lecture RNA-seq overview: transcription, protocols, and applications — Husen Umer
10:00 – 10:45 Lecture Next-generation sequencing for RNA-seq: from sample to libary prep and sequencing — Ruben Diaz Rua
10:45 – 11:00 Coffee Break
11:00 – 12:00 Lecture Seuqencing technology: Illumina — Salim Bougouffa
12:00 – 13:00 Lunch

Module 2: Computational Overview and Data Access

Time Type Topic Tools / Resources Instructor
13:00 – 13:45 Lecture Linux command line refresher and Ibex HPC orientation Ibex, bash Issaac Rajani
13:45 – 14:30 Lab 1 Genomic File Formats — explore FASTA, FASTQ seqkit Bioinforamtics Team
14:30 – 14:45 Coffee Break
14:45 – 16:30 Lab 2 Public Data Retrieval — download GSE136366 FASTQ files and reference genome sra-toolkit, datasets, seqkit Bioinforamtics Team
16:30 – 17:00 Q&A and recap

Day 2 — Monday, 6 April 2026

Module 3: Design, Quality Control and Preprocessing

Time Type Topic Tools / Resources Instructor
09:00 – 09:45 Lecture Experimental design: replication, batch effects, and statisical power — Ikram Ullah
09:45 – 10:30 Interative Lecture Raw data quality evaluation with FastQC FastQC Issaac Rajani
10:30 – 10:45 Coffee Break
10:45 – 11:30 Interative Lecture Quality control & filtering with fastp; ribosomal and contaminant removal fastp Salim Bougouffa
09:45 – 12:00 Lab 3 FastQC, fastp trimming, and MultiQC report — QC of GSE136366 samples FastQC, fastp, MultiQC Bioinforamtics Team
12:00 – 13:00 Lunch

Module 4: Read Alignment

Time Type Topic Tools / Resources Instructor
13:00 – 14:00 Lecture Read alignment vs. pseudoalignment; splice-aware alignment STAR Salim Bougouffa
14:00 – 14:30 Lecture Post-processing aligned reads: sorting, indexing, duplicate marking samtools, Picard Husen Umer
14:30 – 14:45 Coffee Break
14:45 – 16:00 Lab 4 STAR alignment of GSE136366 samples; BAM post-processing and visualization in IGV STAR, samtools, Picard, IGV Bioinforamtics Team
16:00 – 16:30 Lecture Post-alignment QC: strandedness, coverage uniformity, duplication, library complexity RSeQC, QualiMap, dupRadar, PreSeq Salim Bougouffa
16:30 – 17:00 Q&A and recap

Day 3 — Tuesday, 7 April 2026

Module 5: Quantification

Time Type Topic Tools / Resources Instructor
09:00 – 09:45 Lecture Transcript quantification with Salmon Salmon Husen Umer
09:45 – 10:30 Lab 5 Salmon quantification of GSE136366 Salmon, tximport Bioinforamtics Team
10:30 – 10:45 Coffee Break
10:45 – 12:00 Lab 5 Exploratory analysis quantification for sample-level QC Visualization packages Bioinforamtics Team
12:00 – 13:00 Lunch

Module 6: Standardized and Reproducible Analysis I

Time Type Topic Tools / Resources Instructor
13:00 – 14:00 Lecture Nextflow and nf-core overview; nf-core/rnaseq workflow structure and key parameters Nextflow, nf-core workflows Husen Umer
14:00 – 14:45 Lab 6 Samplesheet setup, Singularity containers, and test workflow run nf-core/rnaseq, sbatch Bioinforamtics Team
14:45 – 15:00 Coffee Break
15:00 – 16:30 Lab 6 Configure and run nf-core/rnaseq on GSE136366; inspect MultiQC report and output files nf-core/rnaseq, MultiQC Bioinforamtics Team
16:30 – 17:00 Q&A and recap

Day 4 — Wednesday, 8 April 2026

Module 7: Differential Expression Analysis

Time Type Topic Tools / Resources Instructor
09:00 – 09:45 Lecture Normalization strategies: TPM, FPKM, TMM, DESeq2 size factors DESeq2 Husen Umer
09:45 – 10:30 Lecture Statistical testing: design matrices, contrasts, LFC shrinkage, and confounders DESeq2 Ikram Ullah
10:30 – 10:45 Coffee Break
10:45 – 12:00 Lab 7 DEA in R with DESeq2 — PCA, volcano plots, MA plots, heatmaps of GSE136366 DESeq2Python/R Bioinforamtics Team
12:00 – 13:00 Lunch

Module 8: Functional Enrichment

Time Type Topic Tools / Resources Instructor
13:00 – 14:00 Lecture Enrichment analysis & statisical considerations: ORA vs. GSEA, GO, KEGG pathways clusterProfiler, gsea, org.Hs.eg.db Husen Umer
14:00 – 15:00 Lab 8 GO enrichment, pathway enrichment, and GSEA on GSE136366 DEG results clusterProfiler, Visualization Bioinforamtics Team
14:30 – 14:45 Coffee Break
15:15 – 16:00 Lecture nf-core/differentialabundance overview: input files, contrasts configuration, and output nf-core/differentialabundance Husen Umer
16:00 – 17:00 Lab 9 Configure and run nf-core/differentialabundance on GSE136366; interpret output nf-core/differentialabundance Bioinforamtics Team

Day 5 — Thursday, 9 April 2026

Module 9: Standardized and Reproducible Analysis II

Time Type Topic Tools / Resources Instructor
09:00 – 10:15 Lecture Interpreting the interactive Shiny report and MultiQC DE summary R shiny, MultiQC Husen Umer
10:15 – 10:30 Coffee Break
10:30 – 12:00 Lab Personal or Capstone project setup and execution nf-core workflows Bioinforamtics Team
12:00 – 13:00 Lunch

Module 10: Real-world Analysis Capstone

Time Type Topic Tools / Resources Instructor
13:00 – 13:30 Lecture Capstone overview: end-to-end analysis strategy and interpretation tips — Bioinforamtics Team
13:30 – 15:30 Lab 10 End-to-end analysis of GSE136366 (or your own dataset) — nf-core/rnaseq → DE → enrichment All course tools Bioinforamtics Team
15:30 – 15:45 Coffee Break
15:45 – 16:30 Presentations Participant capstone results and discussion — Everyone
16:30 – 17:00 Closing Course wrap-up, resources, and next steps in bioinformatics — Husen Umer