Course Live Advanced Dr. Omics Edu

Cancer Bioinformatics in R: Bioconductor, TCGA Data & Survival Analysis

A hands-on cancer bioinformatics course covering R, Bioconductor, TCGA data analysis, differential expression, survival analysis, and biological interpretation.

5.0/5
English
Updated Sep 2026

About this course

Cancer Bioinformatics in R: Bioconductor, TCGA Data & Survival Analysis is a practical, hands-on course designed to introduce participants to computational analysis of cancer genomics and transcriptomics data using R and Bioconductor.

Participants will learn how to access and work with publicly available The Cancer Genome Atlas (TCGA) datasets, perform data preprocessing and exploratory analysis, investigate gene-expression patterns, and identify genes associated with cancer phenotypes. The course also introduces statistical and visualization approaches for survival analysis, enabling participants to explore relationships between molecular features and patient survival outcomes.

Through guided practical exercises, participants will work with representative cancer datasets and develop an understanding of how R-based bioinformatics workflows can be used to analyze, visualize, and interpret cancer-related molecular data.

What you will learn

Understand the fundamentals of cancer bioinformatics and computational oncology.

Develop practical skills in R programming for bioinformatics.

Understand the role of Bioconductor in genomic data analysis.

Access and work with publicly available TCGA datasets.

Perform data preprocessing and exploratory analysis.

Analyze cancer gene-expression data using R.

Identify and visualize differentially expressed genes.

Generate and interpret common cancer genomics visualizations.

Understand the principles of survival analysis.

Perform and interpret Kaplan–Meier survival analysis.

Explore associations between gene expression and patient survival.

Interpret computational results in a cancer biology context.

Skills you will gain

R Programming Bioconductor Cancer Bioinformatics TCGA Data Analysis Gene Expression Analysis Data Preprocessing Exploratory Data Analysis Differential Expression Analysis Data Visualization Kaplan–Meier Analysis Survival Analysis Clinical Data Integration Statistical Analysis Genomic Data Interpretation Bioinformatics Workflows

Certification

Available

Issued by Dr. Omics Edu

Course curriculum

1 module

Day 1 – Getting started with R for bioinformatics: RStudio setup, scripts, and basic syntax.
Day 2 – Understanding data types and variables in R (numeric, character, logical, factors).
Day 3 – Efficient data structures for genomic data (vectors, matrices, data frames, lists).
Day 4 – Importing, exporting, and handling biological data (CSV, TSV, FASTA/FASTQ basics).
Day 5 – Control structures for data processing in R (if-else, for/while loops, apply family).
Day 6 – Writing functions for automating bioinformatics workflows.
Day 7 – Managing and utilizing R packages for analysis using Bioconductor.
Day 8 – Data manipulation for genomic and expression data with dplyr and tidyverse.
Day 9 – Visualizing biological data with R-1: basic plots, PCA plots, and Venn diagrams (ggplot2).
Day 10 – Visualizing biological data with R-2: heatmaps, volcano plots, and MA plots.
Day 11 – Bioconductor core: working with SummarizedExperiment for omics data.
Day 12 – Bioconductor core: genomic ranges and interval operations with GRanges.
Day 13 – TCGA data extraction and preparation using TCGAbiolinks.
Day 14 – Cancer survival analysis with survival and survminer (Kaplan-Meier, Cox models).
Day 15 – Publication-ready plots and Complex Heatmaps for multi-omics data presentation.

What you need to start

Basic understanding of molecular biology, genetics, or cancer biology.
Basic computer skills.
Prior R programming experience is helpful but not mandatory.
Basic understanding of statistics is recommended.
No prior experience with TCGA or Bioconductor is required.

Who this course is for

Undergraduate and postgraduate students in Bioinformatics, Biotechnology, Biochemistry, Biology, Genetics, Microbiology, and Life Sciences.
PhD scholars and research students.
Bioinformatics and cancer genomics researchers.
Students interested in learning R-based cancer data analysis.
Researchers working with public cancer genomics datasets.
Life-science professionals looking to develop practical cancer bioinformatics 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

Programming for Cancer Bioinformatics (R)

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 R and Bioconductor exercises.
Practical analysis of representative TCGA datasets.
Step-by-step guidance through cancer data analysis workflows.
Gene-expression analysis and visualization exercises.
Hands-on survival analysis and Kaplan–Meier plots.
Supporting datasets and learning resources.
Course materials for reference and practice.
Certificate of participation/completion as applicable.