JHU EN.601.449/EN.601.649: Computational Genomics: Applied Comparative Genomics

Prof: Michael Schatz (mschatz @ cs.jhu.edu)
TA: Alex Sweeten (asweete1 @ jhu.edu)
Class Hours: Monday + Wednesday @ 3:00p - 4:15p Hodson 311
Schatz Office Hours: By appointment
Sweeten Office Hours: Monday from 4:30pm - 5:30pm (over zoom) and by appointment

The primary goal of the course is for students to be grounded in theory and leave the course empowered to conduct independent genomic analyses. We will study the leading computational and quantitative approaches for comparing and analyzing genomes starting from raw sequencing data. The course will focus on human genomics and human medical applications, but the techniques will be broadly applicable across the tree of life. The topics will include genome assembly & comparative genomics, variant identification & analysis, gene expression & regulation, personal genome analysis, and cancer genomics. The grading will be based on assignments, a midterm exam, class presentations, and a significant class project. There are no formal course prerequisites, although the course will require familiarity with UNIX scripting and/or programming to complete the assignments and course project.

Prerequisites

• Online introduction to Unix/Linux. Students are strongly recommended to complete one of the following online tutorials (or both) before class begins.
  • Code academy's Intro to Unix
  • Rosalind Bioinformatics Programming in Python
  • Minimal Make
• Access to a Linux Machine, and/or Install Docker (Unfortuantely, even Mac will not work correctly for some programs)

Course Resources:

• Syllabus and Policies
• Piazza Discussion Board
• GradeScope Entry Code: JK5VB4
• Fall 2022 Course Materials

Related Courses & Readings

• Applied Comparative Genomics by Aaron Quinlan
• Algorithms for DNA Sequencing by Ben Langmead
• Computational Biology by Rob Patro
• HarvardX Biomedical Data Science
• PLOS Computational Biology Translational Bioinformatics
• Biostars Handbook

Related Textbooks

• Molecular Biology of the Gene (Watson et al)
• Molecular Biology of the Cell (Alberts)
• Biological Sequence Analysis (Durbin et al)
• Modern Statistics for Modern Biology (Holmes & Huber)
• WDL Workflows
• UCSC Genome Browswer

Schedule

Class	Date	Day	Topic	Assignments	Readings
1	28-Aug	Mon	Introduction	Sign Up for Piazza	* Biological data sciences in genome research (Schatz, 2015, Genome Research) * Big Data: Astronomical or Genomical? (Stephens et al, 2015, PLOS Biology)
2	30-Aug	Wed	Genomic Technologies	Assignment 1: Genomic Fundamentals	* Molecular Structure of Nucleic Acid (Watson and Crick, 1953, Nature) * Coming of age: ten years of next-generation sequencing technologies (Goodwin et al, 2016, Nature Reviews Genetics) * Piercing the dark matter: bioinformatics of long-range sequencing and mapping (Sedlazeck et al, 2018, Nature Reviews Genetics)
*	4-Sep	Mon	$${\color{red}\text{Labor Day}}$$
3	6-Sep	Wed	Whole Genome Assembly	Assignment 2: Assembly	* Toward simplifying and accurately formulating fragment assembly. (Myers, 1995, J. Comp. Bio.) * Velvet: Algorithms for de novo short read assembly using de Bruijn graphs (Zerbino and Birney, 2008, Genome Research) *SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing (Bankevich et al. 2012) * Quake: quality-aware detection and correction of sequencing errors (Kelley et al, 2010, Genome Biology) * MUMmer: Alignment of Whole Genomes (Delcher et al, 1999, NAR)
4	11-Sep	Mon	The human genome and intro to long reads		* The complete sequence of a human genome (Nurk et al, 2022 * MHAP: Assembling large genomes with single-molecule sequencing and locality-sensitive hashing (Berlin et al, 2015, Nature Biotech) FALCON-unzip: Phased diploid genome assembly with single-molecule real-time sequencing (Chin et al, 2016, Nature Methods) * Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies (Rhie et al. 2020)
5	13-Sep	Wed	Pan-Genomics		* Approaching complete genomes, transcriptomes and epi-omes with accurate long-read sequencing (Kovaka et al, 2023, Nature Methods * Piercing the dark matter: bioinformatics of long- range sequencing and mapping (Sedlazeck et al, 2018, Nature Reviews Genetics) * A draft human pangenome reference (Liao et al, 2023)
6	18-Sep	Mon	Genomics in the Cloud		* Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) (Schatz et al, 2022, Cell Genomics)
7	20-Sep	Wed	Read Mapping	Assignment 3: Mappability and Mapping	* How to map billions of short reads onto genomes (Trapnell and Salzberg, 2009, Nature Biotech) * Bowtie: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome (Langmead et al, 2009, Genome Biology) * BWA-MEM: Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM (Li, 2013, arXiv) * Sapling: Accelerating Suffix Array Queries with Learned Data Models (Kirsche et al, 2020, bioRxiv
8	25-Sep	Mon	Variant Analysis		* Haplotype-based variant detection from short-read sequencing (Garrison and Marth, arXiv, 2012) * The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data (McKenna et al, 2010, Genome Research) * A universal SNP and small-indel variant caller using deep neural networks (Poplin et al, 2018, Nature Biotechnology * SAM/BAM/Samtools: The Sequence Alignment/Map format and SAMtools (Li et al, 2009, Bioinformatics) * IGV: Integrative genomics viewer (Robinson et al, 2011, Nature Biotech)
9	27-Sep	Wed	Structural Variant Analysis		* Accurate detection of complex structural variations using single-molecule sequencing (Sedlazeck et al, 2018, Nature Methods) * Characterizing the Major Structural Variant Alleles of the Human Genome (Audano et al, 2019, Cell) * Resolving the complexity of the human genome using single-molecule sequencing (Chaisson et al, 2015, Nature)
10	2-Oct	Mon	Sketching		* Mash: fast genome and metagenome distance estimation using MinHash (Ondov et al, 2016, Genome Biology)
11	4-Oct	Wed	Genome Arithmetic and Plane Sweep	Assignment 4: BWT and Modimizers	* BEDTools: a flexible suite of utilities for comparing genomic features (Quinlan & Hall, 2010, Bioinformatics) * A Parallel Algorithm for N-Way Interval Set Intersection (Layer & Quinlan, 2016, IEEE Proceedings)
12	9-Oct	Mon	Machine Learning Primer		* What are decision trees? (Kingsford and Salzberg, 2008, Nature Biotechnology) * What is a hidden Markov model? (Eddy, 2004, Nature Biotechnology) * Deep learning in biomedicine (Wainberg et al, 2018, Nature Biotechnology) * Visualizing Data Using t-SNE
13	11-Oct	Wed	Functional Analysis 1: Annotation	Project Proposal	* BLAST: Basic Local Alignment Search Tool * Glimmer: Microbial gene identification using interpolated Markov models * MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects
14	16-Oct	Mon	Functional Analysis 2: RNA-seq		* RNA-Seq: a revolutionary tool for transcriptomics (Wang et al, 2009. Nature Reviews Genetics) * Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks (Trapnell et al, 2012, Nature Protocols) * Salmon provides fast and bias-aware quantification of transcript expression (Patro et al, 2017, Nature Methods) * Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications (Krueger and Andrews, 2011, Bioinformatics)
15	18-Oct	Wed	Functional Analysis 3: Methyl-seq, Chip-seq, and Hi-C	Assignment 5: Functional Genomics	* ChIP-seq and beyond: new and improved methodologies to detect and characterize protein-DNA interactions (Furey, 2012, Nature Reviews Genetics) * PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls (Rozowsky et al. 2009. Nature Biotech) * Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome (Lieberman-Aiden et al, 2009, Science)
16	23-Oct	Mon	Functional Analysis 4: Regulatory States, ENCODE, GTEx, RoadMap		* An integrated encyclopedia of DNA elements in the human genome (The ENCODE Project Consortium, Nature, 2012) * Genetic effects on gene expression across human tissues (GTEx Consortium, Nature, 2017) * Integrative analysis of 111 reference human epigenomes (Roadmap Epigenome Consortium, Nature, 2015) * ChromHMM: automating chromatin-state discovery and characterization (Ernst & Kellis, 2012, Nature Methods) * Segway: Unsupervised pattern discovery in human chromatin structure through genomic segmentation (Hoffman et al, 2012, Nature Methods)
17	25-Oct	Wed	Functional Analysis 5: Single Cell Genomics		* Ginkgo: Interactive analysis and assessment of single-cell copy-number variations (Garvin et al, 2015, Nature Methods) * The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells (Trapnell et al, Nature Biotech, 2014) * Eleven grand challenges in single-cell data science (Lähnemann et al, Genome Biology, 2020)
18	30-Oct	Mon	Human Evolution	Preliminary Project Report	* An integrated map of genetic variation from 1,092 human genomes (1000 Genomes Consortium, 2012, Nature) * Analysis of protein-coding genetic variation in 60,706 humans (Let et al, 2016, Nature) * A Draft Sequence of the Neandertal Genome (Green et al. 2010, Science) * Excavating Neandertal and Denisovan DNA from the genomes of Melanesian individuals (Vernot et al. 2016. Science)
19	1-Nov	Wed	$${\color{blue}\text{Midterm review}}$$
20	6-Nov	Mon	$${\color{blue}\text{Midterm}}$$	*In class exam*
21	8-Nov	Wed	Human Genetic Diseases		* Genome-Wide Association Studies (Bush & Moore, 2012, PLOS Comp Bio) * The contribution of de novo coding mutations to autism spectrum disorder (Iossifov et al, 2014, Nature)
22	13-Nov	Mon	Cancer Genomics	Prelim Report Due	* The Hallmarks of Cancer (Hanahan & Weinberg, 2000, Cell) * Evolution of Cancer Genomes (Yates & Campbell, 2012, Nature Reviews Genetics) * Comprehensive molecular portraits of human breast tumours (TCGA, 2012, Nature)
23	15-Nov	Wed	Microbiome and Metagenomics		* Kraken: ultrafast metagenomic sequence classification using exact alignments (Wood and Salzberg, 2014, Genome Biology) * Chapter 12: Human Microbiome Analysis (Morgan and Huttenhower)
*	20-Nov	Mon	$${\color{red}\text{Thanksgiving Break}}$$
*	22-Nov	Wed	$${\color{red}\text{Thanksgiving Break}}$$
24	27-Nov	Mon	$${\color{blue}\text{In class project presentation}}$$	Project presentation
25	29-Nov	Wed	$${\color{blue}\text{In class project presentation}}$$	Project presentation
26	4-Dec	Mon	$${\color{blue}\text{In class project presentation}}$$	Project presentation
*	6-Dec	Wed	$${\color{red}\text{No Class}}$$
*	17-Dec	Sun	$${\color{blue}\text{Final Report Due}}$$	Final Report