Course Overview: Welcome to the era of high-resolution genomics. This course is meticulously designed to navigate the complex landscape of RNA sequencing, moving from traditional bulk analysis concepts to the cutting-edge world of Single-Cell RNA-seq (scRNA-seq). Whether you are a biologist wanting to analyze your own data or a data scientist entering the life sciences, this course provides the technical roadmap to understand gene expression at cellular resolution.

What You Will Learn: We have structured the curriculum into 3 distinct modules covering 10 comprehensive classes, taking you from raw data retrieval to advanced cellular trajectory inference.

Module 1: Foundations of Transcriptomics: Build a robust theoretical base. This module covers the Central Dogma, traces the evolution of sequencing technologies, and demystifies the structure of essential file formats (FASTQ, GTF, GFF). You will also gain practical skills in retrieving datasets from public repositories like NCBI GEO and SRA Toolkit.

Module 2: Single-Cell RNA-seq (scRNA-seq) Processing: Step into the future of genomics with a focus on the 10x Genomics platform. This module covers the critical initial steps of the pipeline, teaching you how to process raw reads, perform rigorous Quality Control (QC) to remove low-quality cells, and normalize data for accurate comparison.

Module 3: Advanced Analysis & Interpretation: Master the art of data visualization and biological discovery. Learn to reduce complex data into interpretable maps using PCA, UMAP, and t-SNE. The course guides you through Clustering to find distinct cell populations, Marker Gene Identification for Cell Type Annotation, and advanced Trajectory Analysis (Pseudotime) to trace developmental pathways.

Who Should Attend:

• PhD students and Postdocs in Genomics, Bioinformatics, and Molecular Biology.

• Biomedical researchers interested in 10x Genomics and transcriptomics.

• Data analysts looking to specialize in biological data interpretation.

Outcome: By the end of this course, you will be proficient in handling raw sequencing data, capable of running a complete Single-Cell analysis pipeline, and skilled in generating publication-ready plots to visualize cellular heterogeneity.