Genomics and Bioinformatics
Sequencing genomes and analyzing 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 GINA and HIPAA, 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 American version of this course. See the Canadian 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, analyze 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 27 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 analyzing 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 GINA and HIPAA, Indigenous data governance and reproducible workflows.
Part of the Science stream, typically taken in year 4.