| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Intermediate |
| Duration | 1 Month |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹2249 / $49 |
| Tools | BWA SAMtools GATK FastQC Trimmomatic R/Bioconductor IGV PLINK |
About the Transcriptomics: RNA to Single Cell Applications 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.
Program Highlights
• Comprehensive coverage of Transcriptomics from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Genomics
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Exposure to industry-standard tools and platforms used in Genomics
• Career-oriented training for academic and professional growth in Genomics
Course Curriculum
Module 1: Transcriptomics in System Biology
- RNA Extraction, QC & Sequencing Technologies
- RNA-seq Data Processing & Quality Control
- Transcriptomics Software: FASTQC, STAR, Kallisto
Module 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
Module 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)
Module 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
Tools, Techniques, or Platforms Covered
BWA SAMtools GATK FastQC Trimmomatic R/Bioconductor IGV PLINK
Real-World Applications
- Apply Transcriptomics skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical Genomics competencies
- Solve industry-relevant problems using Transcriptomics methodologies and tools
- Contribute to open-source projects and collaborative research in Genomics
- Prepare for competitive examinations, interviews, and professional certifications in Genomics
Who Should Attend & Prerequisites
- Students pursuing degrees in Genomics, science, engineering, or related disciplines
- Working professionals seeking to upskill or transition into Genomics roles
- Researchers and academicians looking to adopt modern techniques in Genomics
- Entrepreneurs, freelancers, and self-learners interested in practical Genomics knowledge
Certification
