MICROARRAY 30 days · 6 modules · Online

Microarray Data Analysis in R Workshop (30-Day, Online)

Quality control, normalization, linear modeling and pathway enrichment for gene expression arrays in R.

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About this workshop

Microarrays measure gene expression by detecting how much RNA binds to thousands of probes on a chip. Although sequencing has largely replaced them for new experiments, an enormous amount of valuable data in public archives was generated this way, and it can be re-analysed to answer new questions. This workshop teaches the analysis in R and Bioconductor: reading raw intensity files, checking quality and spotting outlier arrays, correcting background and batch effects, and normalising so arrays are comparable. You then fit statistical models to find differentially expressed genes, control false discoveries, map probes to gene names and run enrichment analysis. The final modules show how to shortlist biomarker candidates and how results compare with RNA-Seq.

Tools and pipelines you will use

This workshop emphasizes standard, open-source bioinformatics tools widely used in peer-reviewed genomics literature:

R Project ↗Bioconductor ↗GEOquery ↗oligo ↗limma ↗clusterProfiler ↗ComplexHeatmap ↗

What you will learn

Module 1 Foundations
Week 1
Microarray technology How arrays measure expression.
Experimental design Replicates, controls and batches.
Environment setup Use R and Bioconductor.
Data sources Find and download public array data.
Module 2 Quality control
Raw data inspection Read image-derived intensity files.
Quality plots Boxplots, density and degradation checks.
Outlier detection Identify arrays that should be removed.
Batch effects Detect and correct technical variation.
Module 3 Normalization
Background correction Remove non-specific signal.
Normalization methods Make arrays comparable.
Probe summarization Combine probes into gene values.
Before and after checks Confirm normalization helped.
Module 4 Differential expression
Statistical models Linear models for array data.
Setting up contrasts Define the comparisons you want.
Multiple testing Control false discoveries.
Annotation Map probes to gene names.
Module 5 Interpretation
Volcano plots and heatmaps Present results clearly.
Enrichment analysis Find processes and pathways.
Co-expression and networks Group genes that move together.
Biomarker shortlisting Select candidates for follow-up.
Module 6 Mini-project and report
Week 4
Project dataset Analyse a public array dataset.
Reproducible workflow Record every step and setting.
Figures and write-up Present findings.
Review and next steps Discuss validation and comparison with RNA-Seq.

What you receive & prerequisites

What you receive

  • 30 days of structured online self-paced access & mentor guidance
  • Curated real-world NGS benchmark datasets
  • Reusable pipeline scripts and command-line code templates
  • Independent capstone mini-project evaluation
  • Certificate of Completion issued by Xenoi Biotech Pvt. Ltd.

Prerequisites & setup

  • Basic life science background (B.Sc., M.Sc., B.Tech, or research scholar)
  • No prior programming or Linux experience required (covered in Module 1)
  • Laptop or PC with 8 GB RAM and internet access
  • Remote compute setup instructions provided during onboarding

Course curriculum designed by Anjali Chaudhary, Bioinformatics Scientist at Xenoi Biotech.

Last updated: October 2026

Related workshops & services

Broaden your computational biology expertise with complementary workshops:

Need this analysis done for your laboratory data? Explore our Genomics Services or consult on Custom Bioinformatics Pipelines.

Frequently asked questions

Is this Microarray Data Analysis workshop delivered online?

Yes. All Xenoi Biotech workshops are delivered 100% online, allowing researchers and students across India and internationally to participate with remote compute support.

How long is the workshop and what is the workload?

The workshop runs for 30 days across 6 structured modules. Learners typically dedicate 1 to 2 flexible hours per day to work through pipeline commands, code exercises, and the mini-project.

Who is this workshop designed for?

It is built for B.Sc., M.Sc., and Ph.D. students, postdoctoral researchers, faculty members, and industry professionals in biotechnology, biochemistry, microbiology, and medicine who need to analyze NGS datasets independently.

What will I learn in this workshop?

You will learn to retrieve public datasets from NCBI GEO with GEOquery, perform RMA background correction and quantile normalization in oligo, model complex multi-factor designs in limma, control FDR, and run pathway enrichment with clusterProfiler.

What are the fees, dates, and enrollment details?

The workshop fee is MRP ₹5,000, inclusive of GST. Batch dates are shared on enquiry. Use the Enrol now button to reserve your place or receive the upcoming schedule.

Fees, dates and batches

The workshop fee is MRP ₹5,000 (incl. GST). Batch dates and onboarding materials are shared upon enquiry.

Enquire about this workshop ↗