Transcriptomic Insights: A Hands-On Bulk RNA-Seq Training Program
Overview:
Omics Minder invites you to a specialized 5-day intensive workshop on bulk RNA-Seq data analysis. Designed for researchers, students, and professionals in the life sciences, this course offers a practical, step-by-step approach to mastering RNA-Seq — from data acquisition to biological interpretation.
Participants will engage in both theoretical sessions and hands-on labs using real-world datasets and tools widely adopted in the field.
Workshop Structure:
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5 Days
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Session Format:
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2 Hours Lecture
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2 Hours Guided Practical Application
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Live Online Sessions (Zoom)
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Course Fee: 1500 EGP
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Certificate of Completion Provided
Key Learning Outcomes:
Participants will gain practical experience in:
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RNA-Seq experimental design and setup
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Data quality control using FastQC and MultiQC
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Read trimming and preprocessing (Trimmomatic / Cutadapt)
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Alignment with STAR or HISAT2
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Gene quantification using FeatureCounts
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Differential expression analysis with DESeq2 and edgeR
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Functional enrichment (GO, KEGG) using clusterProfiler and related tools
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Data visualization and reporting in RMarkdown
Day-by-Day Breakdown:
Day 1 – Introduction & Experimental Design
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RNA-Seq applications and experimental planning
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Biological replicates, batch effects, and read depth
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Setting up analysis tools and accessing public datasets
Day 2 – Quality Control & Preprocessing
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Assessing read quality, adapter content, and duplication levels
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Trimming and filtering strategies
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FastQC, MultiQC, and trimming workflows
Day 3 – Alignment & Quantification
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Reference genome selection and annotation formats
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Read alignment and count matrix generation
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STAR/HISAT2 and FeatureCounts pipelines
Day 4 – Differential Expression Analysis
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Statistical modeling with DESeq2 and edgeR
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Normalization, dispersion estimation, and fold-change analysis
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Identifying significant genes and visualizing results
Day 5 – Functional & Pathway Analysis
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GO and KEGG enrichment analysis
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Clustering, PCA, heatmaps
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Building reproducible reports with RMarkdown
Target Audience :
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Graduate and postgraduate students in life sciences
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Researchers working with transcriptomic data
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Professionals in genomics, molecular biology, or bioinformatics
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Anyone interested in acquiring reproducible RNA-Seq analysis skills
Prerequisites :
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No prior experience in R or programming is required.
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Participants will be guided step-by-step through the necessary tools and scripting components during the hands-on sessions. Basic familiarity with molecular biology or genomics is recommended to get the most out of the course content.