Cancer Transcriptomics & Data Analysis
Unlock insights into tumor progression and biomarker discovery by mastering RNA-Seq data analysis.
Decoding the Transcriptome of Cancer
With advancements in Next-Generation Sequencing (NGS), RNA sequencing (RNA-Seq) has become the gold standard for quantifying gene expression. In oncology, this has revolutionized research, allowing scientists to identify which genes are active in tumor cells and discover critical biomarkers for early diagnosis and targeted therapies. Cancer transcriptomics provides a detailed snapshot of gene behavior during tumor progression, offering profound insights into the underlying biology of the disease.
To harness this powerful technology, researchers need specialized skills in data analysis. This workshop is designed to equip you with the essential expertise to handle and process complex RNA-Seq data. By exploring powerful tools like R and Bioconductor and working with real-world datasets from portals like The Cancer Genome Atlas (TCGA), you will gain the confidence to conduct sophisticated cancer transcriptomics research.
Key Features & Benefits
Master R & Bioconductor
Gain in-depth skills in R programming and the Bioconductor suite, the industry standard for genomic data analysis.
Real Cancer Datasets
Get hands-on experience by retrieving and analyzing data directly from public repositories like SRA and the TCGA portal.
End-to-End Workflow
Learn the complete analysis pipeline, from raw data QC and alignment to differential expression and pathway analysis.
Industry-Relevant Case Study
Apply your knowledge to a relevant case study, ensuring you can translate theory into practice.
What You Will Learn
Module 1: Foundations
- Bioinformatics Basics: Get an introduction to bioinformatics and an overview of the cancer transcriptomics landscape.
- Public Data Retrieval: Learn to navigate and access important public cancer datasets.
Module 2: R Programming Essentials
- Core R Skills: Understand R objects, file operations, and data manipulation.
- Data Visualization: Create insightful plots and graphs to visualize complex data.
- Introduction to Bioconductor: Get acquainted with this essential suite of tools for genomic analysis.
Module 3: Working with TCGA Data
- Exploring the TCGA Portal: Learn to navigate The Cancer Genome Atlas and understand its data formats.
- Automated Data Retrieval: Use the TCGAbiolinks package in R to programmatically download and prepare data.
Module 4: RNA-Seq Data Analysis Workflow
- NGS Data Overview: Understand file formats and standard tools for RNA-Seq.
- Data Processing: Perform read alignment, counting, and data normalization.
- Differential Gene Expression: Use DESeq2 to identify differentially expressed genes (DEGs).
- Functional Analysis: Visualize DEGs, filter results, and perform Gene Set Enrichment Analysis (GSEA) using tools like DAVID.
- A Brief Introduction to Single-Cell Transcriptomics.
Workshop Details
Date & Time
17 November to 16 December 2025
Every Monday and Tuesday
6:30 to 8:00 PM IST (GMT+5:30)
Additional Information
The workshop will be conducted online via Zoom.
Each candidate will be awarded with an e-certificate.
For further queries: +91 7021386045 (WhatsApp) or training@genespectrum.in