Genomics and Bioinformatics
Sequencing genomes and analysing them computationally: genome biology from the Human Genome Project to telomere-to-telomere genomes and pangenomes, short- and long-read sequencing, FASTQ and Phred qualities, read processing, coverage and k-mer spectra, de Bruijn and overlap assembly and assembly evaluation, dynamic programming alignment, substitution matrices, E-values and BLAST, Burrows–Wheeler and FM-index read mapping and SAM files, genotype likelihoods, VCF and variant interpretation, hidden Markov models and genome annotation, RNA-seq normalization, negative binomial testing and false discovery rates, single-cell analysis, comparative genomics, orthology and dN/dS, protein structure prediction, functional genomics, metagenomics and wastewater surveillance, and genomic medicine, privacy under the Genetic Non-Discrimination Act, Indigenous data governance and reproducible workflows.
BIOL-410 Year 4 3 credits 12 lessons · 5 h 18 min
Offered by HSM University · Biology
This is the Canadian version of this course. See the American version.
What you'll learn
- Describe how genomes vary in size and organization, trace the history from the Human Genome Project to complete telomere-to-telomere genomes and pangenomes, and use standard file formats and public databases.
- Compare short-read and long-read sequencing technologies, explain library preparation and its artifacts, and interpret FASTQ files and Phred quality scores.
- Assess read quality, trim reads appropriately, apply the Lander–Waterman coverage model, and use k-mer spectra to estimate genome size, heterozygosity and error content.
- Explain overlap–layout–consensus and de Bruijn graph assembly, why repeats limit assembly, and evaluate assemblies by contiguity, completeness and correctness.
- Derive and apply global and local alignment by dynamic programming with substitution matrices and affine gaps, interpret E-values and bit scores, and use BLAST and multiple alignment appropriately.
- Explain how the Burrows–Wheeler transform, FM-index and minimizer chaining enable read mapping, and interpret SAM fields, mapping quality and reference bias.
- Calculate genotype likelihoods, interpret VCF records, filter and benchmark variant calls, distinguish germline from somatic and structural variants, and apply the ACMG/AMP classification framework.
- Describe structural and functional genome annotation, implement and interpret hidden Markov model algorithms, and work correctly with GFF3, BED and Gene Ontology annotations.
- Design RNA-seq experiments, normalize counts for depth, length and composition, model overdispersed counts, control the false discovery rate and outline single-cell analysis.
- Compare genomes through whole-genome alignment, synteny, orthology and duplication analysis, estimate dN/dS, and explain phylogenomic methods and prokaryotic pangenomes.
- Explain protein structure prediction, functional genomics assays, CRISPR screens, metagenomics and pathogen and wastewater surveillance, including their main limitations.
- Apply genomics to clinical cases with inheritance-based filtering, analyse the privacy, legal, Indigenous governance and biosecurity issues of genomic data, and build reproducible analysis workflows.
Course content
12 lessons · 5 h 18 min total · final exam
- 1 Genomes and the genomics revolution 25 min · quiz
- 2 Sequencing technologies and sequence data 25 min · quiz
- 3 Read processing, k-mers and coverage 26 min · quiz
- 4 Genome assembly 25 min · quiz
- 5 Pairwise alignment and database search 26 min · quiz
- 6 Read mapping and indexing 26 min · quiz
- 7 Variants: calling, formats and interpretation 27 min · quiz
- 8 Genome annotation and hidden Markov models 27 min · quiz
- 9 Transcriptomics: RNA-seq and differential expression 28 min · quiz
- 10 Comparative genomics and phylogenomics 28 min · quiz
- 11 Structural, functional and metagenomics 26 min · quiz
- 12 Capstone: genomic medicine, data governance and a reproducible analysis 29 min · quiz
- E Final exam 20 questions
Requirements
Recommended background. You can start any course at any time.
Description
Sequencing genomes and analysing them computationally: genome biology from the Human Genome Project to telomere-to-telomere genomes and pangenomes, short- and long-read sequencing, FASTQ and Phred qualities, read processing, coverage and k-mer spectra, de Bruijn and overlap assembly and assembly evaluation, dynamic programming alignment, substitution matrices, E-values and BLAST, Burrows–Wheeler and FM-index read mapping and SAM files, genotype likelihoods, VCF and variant interpretation, hidden Markov models and genome annotation, RNA-seq normalization, negative binomial testing and false discovery rates, single-cell analysis, comparative genomics, orthology and dN/dS, protein structure prediction, functional genomics, metagenomics and wastewater surveillance, and genomic medicine, privacy under the Genetic Non-Discrimination Act, Indigenous data governance and reproducible workflows.
Part of the Science stream, typically taken in year 4.