Transcriptomics: RNA to Single Cell Applications
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Course Overview
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 Syllabus
Module 1
About
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.
Module 3
Program Objectives
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Grasp core principles of RNA biology and transcriptome profiling.
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Master RNA extraction, sequencing workflows, and data preprocessing.
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Utilize industry-standard tools for single-cell data analysis.
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Interpret transcriptomic outputs in disease modeling and therapeutic targeting.
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Develop a research-ready mindset and pipeline in DeepTech biology.
Module 4
Program Structure
Module 5
Week 1: Transcriptomics in System Biology
- RNA Extraction, QC & Sequencing Technologies
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RNA-seq Data Processing & Quality Control
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Transcriptomics Software: FASTQC, STAR, Kallisto
Module 6
Week 2: RNA-seq Data Analysis
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Read Mapping & Genome Annotation (using HISAT2, Ensembl)
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Quantification of Gene Expression (TPM, FPKM, raw counts)
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Data Normalization Techniques for Transcriptomic Integrity
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Statistical & Machine Learning Approaches to Differential Expression Analysis
Module 7
Week 3: Single Cell Transcriptomics
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Introduction to Single Cell RNA-seq (10x Genomics, Smart-seq2)
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Protocols for Single Cell Library Prep & Barcoding
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Processing Pipelines: Cell Ranger, Seurat, Scanpy
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Visualizing Cell Clusters & Gene Markers (UMAP, t-SNE)
Module 8
Week 4: Advanced Transcriptomic Applications
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Spatial Transcriptomics & Tissue Mapping Technologies
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Multi-Omics Integration: Proteomics, Metabolomics & RNA-seq
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Translational Case Studies in Cancer, Neuroscience, and Immunology
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DeepTech Trends: AI in Transcriptomics, Synthetic Biology Intersections
Module 9
Intended For
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Life science graduates, postgraduates, and PhD students in biotech, genetics, or bioinformatics
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Researchers, lab professionals, and R&D executives in genomics & molecular diagnostics
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Medical professionals exploring precision medicine, genomic data interpretation, and translational bioinformatics
Module 10
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
Module 11
Recomended Mentors
Module 12
Fee Structure
Standard Fee: INR 8,998 USD 198
Discounted Fee: INR 4499 USD 99
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of CurrenciesModule 13
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