Course Live Advanced Dr. Omics Edu

Transcriptomic Profiling Masterclass: From GEO Raw CEL Files to Cytoscape Networks

A hands-on transcriptomics masterclass covering GEO microarray CEL files, preprocessing, differential expression, functional analysis, and Cytoscape-based gene network visualization.

5.0/5
English
Updated Sep 2026

About this course

Transcriptomic Profiling Masterclass: From GEO Raw CEL Files to Cytoscape Networks is a practical, hands-on course designed to introduce participants to the complete workflow of transcriptomic analysis using publicly available GEO microarray datasets.

Participants will learn how to retrieve and process raw CEL files, perform quality assessment and preprocessing, normalize expression data, identify differentially expressed genes, and visualize transcriptomic patterns. The course further covers functional enrichment and gene interaction network analysis, followed by visualization and exploration of biologically relevant networks using Cytoscape.

Through guided practical exercises, participants will work with representative GEO datasets and learn how to transform raw microarray data into meaningful gene-expression results, biological pathways, and gene interaction networks.

What you will learn

Understand the fundamentals of transcriptomic and microarray data analysis.

Retrieve and work with raw CEL files from the GEO database.

Perform quality assessment and preprocessing of microarray data.

Understand background correction, normalization, and expression summarization.

Identify differentially expressed genes between experimental conditions.

Generate and interpret common transcriptomic visualizations.

Perform functional enrichment and pathway analysis.

Construct and analyze gene interaction networks.

Import and visualize biological networks using Cytoscape.

Interpret transcriptomic and network-analysis results in a biological context.

Skills you will gain

Transcriptomic Data Analysis Microarray Data Analysis GEO Database CEL File Processing Quality Control Data Preprocessing Normalization Differential Gene Expression Statistical Analysis Gene Annotation Functional Enrichment Pathway Analysis Gene Interaction Networks STRING Cytoscape Network Visualization Biological Interpretation

Certification

Available

Issued by Dr. Omics Edu

Course curriculum

1 module

Day 1 – Introduction to microarray technology and platform types (Affymetrix).
Day 2 – Mining and downloading datasets from GEO (Gene Expression Omnibus).
Day 3 – Understanding raw microarray data structures (CEL files) and experimental design considerations.
Day 4 – Quality assessment using NUSE (Normalized Unscaled Standard Error) plots.
Day 5 – Quality assessment using RLE (Relative Log Expression) plots and identifying outlier arrays.
Day 6 – RMA normalization fundamentals using oligo/affy packages.
Day 7 – Differential expression analysis setup with limma (design matrix, contrasts).
Day 8 – Running limma analysis and interpreting moderated t-statistics/eBayes results.
Day 9 – Probe annotation and ID mapping (probe-to-gene symbol conversion).
Day 10 – Cross-platform validation: comparing microarray results with RNA-Seq data.
Day 11 – Advanced visualization: volcano plots and MA plots for DE results.
Day 12 – Advanced visualization: ComplexHeatmap for expression patterns and sample annotations.
Day 13 – Functional enrichment analysis with clusterProfiler (ORA) and GSEA methodology.
Day 14 – Pathway and network biology using STRING and Cytoscape for interpreting gene networks.
Day 15 – Doubt session

What you need to start

Basic understanding of molecular biology, genetics, or gene expression.
Basic knowledge of bioinformatics concepts is recommended.
Familiarity with Linux or R is helpful but not mandatory.
Basic computer skills.
No prior experience with GEO or Cytoscape is required.

Who this course is for

Undergraduate and postgraduate students in Bioinformatics, Biotechnology, Biochemistry, Microbiology, Biology, Genetics, and Life Sciences.
PhD scholars and research students.
Researchers working with transcriptomic or microarray datasets.
Bioinformatics students and beginners interested in gene-expression analysis.
Life-science professionals looking to develop practical transcriptomics and network-analysis skills.

INR

₹45000

~~₹60000~~ 25% off

USD

$600

~~$700~~ 14% off

Indian learners pay in INR; international learners are billed in USD.

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Paying from outside India? Use this link to complete your payment.

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Active batch

Open for enrolment

Cancer Gene Expression Profiling (Microarray Workflow)

Starts 19 Oct 2026
Ends 06 Nov 2026
Timing 7:00 PM – 8:00 PM
Days Mon, Tue, Wed, Thu, Fri
Platform MS Teams

This course includes

Format Live
Level Advanced
Language English
Modules 1
Certificate Yes
Provider Dr. Omics Edu
Live
instructor-led interactive sessions.
Hands-on analysis using representative GEO microarray datasets.
Practical experience with raw CEL files and transcriptomic workflows.
Step-by-step guidance through preprocessing and differential expression analysis.
Functional enrichment and pathway-analysis exercises.
Hands-on STRING and Cytoscape network analysis.
Supporting datasets and learning resources.
Course materials for reference and practice.
Certificate of participation/completion as applicable.