Self Paced

Transcriptomics: RNA to Single Cell Applications

Decoding the Language of Cells: From RNA to Revolutionary Insights

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Early access to the e-LMS platform is included

  • Mode: Online/ e-LMS
  • Type: Self Paced
  • Level: Moderate
  • Duration: 1 Month

About This Course

This DeepScience-powered, self-paced certificate course delivers a structured journey through the fast-evolving domain of transcriptomics—from RNA sequencing (RNA-seq) fundamentals to cutting-edge single-cell transcriptomics and spatial gene expression technologies. Participants will explore how transcriptomic data unlocks insights into gene regulation, disease biomarkers, and precision medicine.

Designed with real-world application in mind, this course bridges molecular biology with computational genomics. Through expert-led lectures, case studies, and tool-based walkthroughs, you’ll gain actionable skills in biological data science and modern bioinformatics workflows.

Aim

To build interdisciplinary expertise in transcriptomic sciences, enabling participants to:

  • Decode gene expression dynamics.
  • Apply AI-ready bioinformatics pipelines.
  • Transition into cutting-edge biotech and research roles.

Program Objectives

  • Grasp core principles of RNA biology and transcriptome profiling.

  • Master RNA extraction, sequencing workflows, and data preprocessing.

  • Utilize industry-standard tools for single-cell data analysis.

  • Interpret transcriptomic outputs in disease modeling and therapeutic targeting.

  • Develop a research-ready mindset and pipeline in DeepTech biology.

Program Structure

Week 1: Transcriptomics in System Biology

  • RNA Extraction, QC & Sequencing Technologies
  • RNA-seq Data Processing & Quality Control

  • Transcriptomics Software: FASTQC, STAR, Kallisto

Week 2: RNA-seq Data Analysis

  • Read Mapping & Genome Annotation (using HISAT2, Ensembl)

  • Quantification of Gene Expression (TPM, FPKM, raw counts)

  • Data Normalization Techniques for Transcriptomic Integrity

  • Statistical & Machine Learning Approaches to Differential Expression Analysis

Week 3: Single Cell Transcriptomics

  • Introduction to Single Cell RNA-seq (10x Genomics, Smart-seq2)

  • Protocols for Single Cell Library Prep & Barcoding

  • Processing Pipelines: Cell Ranger, Seurat, Scanpy

  • Visualizing Cell Clusters & Gene Markers (UMAP, t-SNE)

Week 4: Advanced Transcriptomic Applications

  • Spatial Transcriptomics & Tissue Mapping Technologies

  • Multi-Omics Integration: Proteomics, Metabolomics & RNA-seq

  • Translational Case Studies in Cancer, Neuroscience, and Immunology

  • DeepTech Trends: AI in Transcriptomics, Synthetic Biology Intersections

Who Should Enrol?

  • Life science graduates, postgraduates, and PhD students in biotech, genetics, or bioinformatics

  • Researchers, lab professionals, and R&D executives in genomics & molecular diagnostics

  • Medical professionals exploring precision medicine, genomic data interpretation, and translational bioinformatics

Program Outcomes

  • Comprehensive expertise in RNA-seq and single-cell transcriptomics
  • Proficiency in cutting-edge tools like Seurat, DESeq2, Cell Ranger, and Scanpy
  • Ability to design, analyze, and visualize transcriptomic experiments
  • Readiness for advanced roles in DeepTech-driven biotech, computational biology, and genomics research

Fee Structure

Standard: ₹8,998 | $198

Discounted: ₹4499 | $99

We accept 20+ global currencies. View list →

What You’ll Gain

  • Full access to e-LMS
  • Real-world dry lab projects
  • One-on-one project guidance
  • Publication opportunity
  • Self-assessment & final exam
  • e-Certificate & e-Marksheet

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★★★★★

The subject matter is very important for my profession but the course did not meet my expectations. All the information shown was information that is found in basic courses on the internet. There was no practical session as such but it showed some results that I already had and where the script that was shown indicated an error.

I am disappointed with the course.

Christian Tutiven
★★★★★

Best delivery

Akashi Sharma
★★★★★
In Silico Molecular Modeling and Docking in Drug Development

Very well structured and presented lectures.

Iva Valkova
★★★★★
AI-Powered Multi-Omics Data Integration for Biomarker Discovery

Great course. Thank you very much.

Abdul Mueed Hafiz

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