Genome Sequencing Course

Lesson 1 • Introduction to Bioinformatics Concepts

Introduces sequence representation, file formats, and computational thinking. Prepares students for the data-handling demands of downstream sequencing analysis.

Lesson 2 • Genome Organization and Complexity

Examines how genomes are packaged, annotated, and classified across organisms. Connects genome size and structure to sequencing strategy selection.

Lesson 3 • Central Dogma and Gene Expression

Explains transcription, translation, and regulatory mechanisms. Grounds students in why sequencing both DNA and RNA is scientifically valuable.

Lesson 4 • DNA Structure and Chemical Composition

Covers nucleotide chemistry, base pairing, and double-helix architecture. Provides the molecular foundation for understanding how sequencing reads DNA.

Lesson 1 • Sample Types and Collection Protocols

Reviews biological sources including blood, tissue, saliva, and environmental samples. Proper collection directly determines downstream DNA quality and sequencing success.

Lesson 2 • DNA Extraction Methods

Compares phenol-chloroform, column-based, and magnetic bead extraction approaches. Method choice affects fragment length, purity, and compatibility with sequencing platforms.

Lesson 3 • DNA Quality Assessment

Teaches spectrophotometric, fluorometric, and electrophoretic quality checks. Quantification and integrity metrics gate samples before library preparation begins.

Lesson 4 • Library Preparation Fundamentals

Covers DNA fragmentation, end-repair, adapter ligation, and size selection. These steps convert raw DNA into platform-compatible sequencing libraries.

Lesson 1 • Emerging and Specialized Sequencing Methods

Surveys optical mapping, linked-read, and single-cell sequencing approaches. Awareness of specialized methods expands the toolkit for complex genomic questions.

Lesson 2 • Sequencing Platform Selection Criteria

Provides a decision framework based on read length, accuracy, cost, and turnaround time. Matching platform to scientific question prevents wasted resources and failed experiments.

Lesson 3 • Long-Read Sequencing Technologies

Covers single-molecule real-time and nanopore sequencing principles and error profiles. Long reads resolve repetitive regions and structural variants inaccessible to short reads.

Lesson 4 • Short-Read Next-Generation Sequencing

Details sequencing-by-synthesis chemistry, cluster generation, and base calling. Short-read platforms dominate clinical and population genomics due to high accuracy and throughput.

Lesson 1 • Sequencing Depth and Coverage Analysis

Defines coverage depth, uniformity, and breadth metrics for whole-genome and targeted sequencing. Adequate and uniform coverage is prerequisite to reliable variant detection.

Lesson 2 • Read Trimming and Filtering

Applies adapter trimming, quality trimming, and length filtering to improve downstream alignment. Aggressive trimming can reduce sensitivity, so thresholds must be calibrated carefully.

Lesson 3 • Quality Assessment of Raw Reads

Uses tools to visualize per-base quality, GC content, duplication rates, and adapter contamination. Quality reports guide trimming decisions and flag failed sequencing runs.

Lesson 4 • Understanding Raw Sequencing Output

Explains FASTQ files, base quality encoding, and run metrics from sequencing instruments. Interpreting raw output is the first step in every bioinformatics workflow.

Lesson 1 • Long-Read Alignment Strategies

Addresses minimap2 and other splice-aware aligners optimized for noisy long reads. Long-read alignment requires different error tolerance and gap penalty settings.

Lesson 2 • Alignment Quality Evaluation

Assesses mapping rate, insert size distribution, and coverage uniformity from aligned BAM files. Poor alignment metrics indicate library or reference problems requiring intervention.

Lesson 3 • Reference Genome Selection and Preparation

Covers reference genome versions, assemblies, and annotation sources. Choosing the correct reference prevents systematic mapping errors and annotation mismatches.

Lesson 4 • Short-Read Alignment Algorithms

Explains Burrows-Wheeler transform, seed-and-extend, and Smith-Waterman alignment strategies. Algorithm choice affects speed, sensitivity, and accuracy for different read types.

Lesson 1 • Principles of Variant Calling

Explains probabilistic models, genotype likelihoods, and haplotype-based calling approaches. Understanding the statistical basis of variant calling is essential for interpreting results.

Lesson 2 • Structural Variant and CNV Detection

Detects deletions, duplications, inversions, and translocations using read-pair and depth signals. Structural variants require specialized callers beyond standard SNP pipelines.

Lesson 3 • Variant Annotation and Prioritization

Annotates variants with functional impact, population frequency, and clinical databases. Annotation transforms a raw variant list into biologically and clinically interpretable findings.

Lesson 4 • Variant Filtering and Quality Metrics

Applies hard filters and variant quality score recalibration to remove false positives. Filtering thresholds must balance sensitivity and specificity for the intended application.

Lesson 1 • De Novo Assembly Principles

Explains overlap-layout-consensus and de Bruijn graph assembly strategies. Assembly approach selection depends on read length, coverage depth, and genome complexity.

Lesson 2 • Assembly Quality Assessment

Evaluates assemblies using N50, BUSCO completeness, and reference-based metrics. Quality assessment determines whether an assembly is suitable for downstream annotation and comparison.

Lesson 3 • Comparative Genomics and Phylogenomics

Aligns multiple genomes to identify conserved regions, synteny blocks, and evolutionary relationships. Comparative analysis reveals functional constraints and species-specific adaptations.

Lesson 4 • Genome Annotation

Predicts genes, repeats, and functional elements using ab initio and evidence-based methods. Accurate annotation is prerequisite to comparative and functional genomic analyses.

Lesson 1 • Cancer Genomics Applications

Applies somatic variant calling, tumor mutational burden, and fusion detection to oncology. Cancer sequencing informs targeted therapy selection and treatment monitoring.

Lesson 2 • Clinical Sequencing Standards and Validation

Covers analytical validation, proficiency testing, and quality management for clinical sequencing. Regulatory compliance requires documented sensitivity, specificity, and reproducibility metrics.

Lesson 3 • Population and Pharmacogenomics Studies

Designs large-scale sequencing studies for GWAS, ancestry inference, and drug response prediction. Population genomics requires careful handling of population stratification and consent.

Lesson 4 • Reporting and Clinical Communication

Structures genomic reports for clinicians, including variant classification, evidence grading, and recommendations. Clear communication of uncertainty is as important as reporting findings.