About Workshop
Aim
What Participants Will Learn
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Understand the RNA-Seq workflow from sequencing to biological inference
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Learn to perform sequence quality control and read alignment
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Explore normalization techniques and statistical analysis using DESeq2
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Visualize results with heatmaps, volcano plots, and pathway analysis
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Gain confidence in interpreting and presenting differential expression data
Structure
- RNA seq and DGE analysis
- Obtaining Data, Data formats
- Sequence quality Check
- Mapping and Quantification of Reads
- Count Normalization
- Differential gene expression analysis DESeq2
- Heat Map and Volcano plot using R
- Enrichment analysis
Important Dates
Registration Ends
Workshop Dates
What You Will Gain

Outcomes
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Clear understanding of RNA-Seq experimental design and pipelines
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Familiarity with common tools: FastQC, STAR, HTSeq, DESeq2
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Hands-on practice with R-based visualizations
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Competence in interpreting gene expression changes
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Ability to run basic enrichment and pathway analysis
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Readiness to apply skills in academic or industry settings
Who Should Attend
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B.Tech / B.Sc / M.Sc / M.Tech graduates or final-year students from Biotechnology, Bioinformatics, Life Sciences, or allied disciplines
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Professionals and researchers working in Genomics, Molecular Biology, Pharmaceutical R&D, or related areas
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Enthusiasts and learners interested in Transcriptomics, Computational Biology, or exploring careers in bioinformatics
DR. SUBARNA THAKUR
Assistant Professor
Speciality: RNA-Seq, DESeq2, Bioinformatics, R Programming
