De Bruijn Graphs for Genome Assembly

Assembling genomes from massive sequencing datasets is one of the most critical challenges in computational biology. Understanding how to represent and resolve these sequence fragments using graph theory is essential for any aspiring bioinformatician. This course guides you through the fundamental theory and practical mechanics of genome assembly using De Bruijn graphs. You will learn how to break down DNA sequences into k-mers, build overlap representations, and construct De Bruijn graphs step-by-step through clear written explanations and structured text-based exercises. We also cover modern considerations such as handling sequencing errors and choosing optimal k-mer lengths to ensure robust assemblies. What you'll learn: - Understand the foundational role of k-mers and graph theory in computational genomics - Construct De Bruijn graphs from raw k-mer compositions systematically - Analyze Eulerian and Hamiltonian paths to resolve genome assembly puzzles - Apply error-correction concepts to handle sequencing noise and chimeric reads - Evaluate how different k-mer sizes affect assembly connectivity and resolution - Read and interpret standard genomic data formats used in assembly pipelines We begin with core terminology and the basic biological context of sequencing before moving into the step-by-step construction of graphs and path-finding algorithms. This course is designed for beginners in bioinformatics, computer science students, or biology enthusiasts with no prior experience in graph-based assembly. Start reading today to demystify the algorithms powering modern genomic discovery.