RNA Seq Differential Expression Analysis

Understand the RNA-Seq workflow from sequencing to biological inference

Learn to perform sequence quality control and read alignment

Explore normalization techniques and statistical analysis using DESeq2

Visualize results with heatmaps, volcano plots, and pathway analysis

Gain confidence in interpreting and presenting differential expression data

Clear understanding of RNA-Seq experimental design and pipelines

Familiarity with common tools: FastQC, STAR, HTSeq, DESeq2

Hands-on practice with R-based visualizations

Competence in interpreting gene expression changes

Ability to run basic enrichment and pathway analysis

Readiness to apply skills in academic or industry settings

B.Tech / B.Sc / M.Sc / M.Tech graduates or final-year students from Biotechnology, Bioinformatics, Life Sciences, or allied disciplines

Professionals and researchers working in Genomics, Molecular Biology, Pharmaceutical R&D, or related areas

Enthusiasts and learners interested in Transcriptomics, Computational Biology, or exploring careers in bioinformatics