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

Prof: Michael Schatz (mschatz @ cs.jhu.edu)
TA: Matthew Nguyen (mnguye99 @ jh.edu)
Class Hours: Monday + Wednesday @ 3:00p - 4:15p Hodson 316
Schatz Office Hours: By appointment
Nguyen Office Hours: TBD and by appointment

The primary goal of the course is for students to be grounded in the fundamental theory and applications to 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. A major focus will be on deep learning and machine learning to tackle these problems. 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: Z3J8YV
• Fall 2023 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	26-Aug	Mon	Introduction	Sign Up for Piazza	* Molecular Structure of Nucleic Acid (Watson and Crick, 1953, Nature) * Biological data sciences in genome research (Schatz, 2015, Genome Research) * Big Data: Astronomical or Genomical? (Stephens et al, 2015, PLOS Biology)
2	28-Aug	Wed	Genomic Technologies, kmers	Assignment 1	* Coming of age: ten years of next-generation sequencing technologies (Goodwin et al, 2016, Nature Reviews Genetics) * Guide to k-mer approaches for genomics across the tree of life (Jenike et al., 2024, arXiv)
*	2-Sep	Mon	$${\color{red}\text{Labor Day}}$$
3	4-Sep	Wed	Assembly, WGA		* 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, J Comput Biol) * MUMmer: Alignment of Whole Genomes (Delcher et al, 1999, NAR)
4	9-Sep	Mon	Human Genome, Long Reads	Assignment 2	* Initial sequencing and analysis of the human genome (International Human Genome Sequencing Consortium, 2001, Nature) * FALCON-unzip: Phased diploid genome assembly with single-molecule real-time sequencing (Chin et al, 2016, Nature Methods) * MHAP: Assembling large genomes with single-molecule sequencing and locality-sensitive hashing (Berlin et al, 2015, Nature Biotech) * Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation (Koren et al, 2017, Genome Research) * Telomere-to-telomere assembly of diploid chromosomes with Verkko (Rautiainen et al, 2023, Nature Biotechnology) * Piercing the dark matter: bioinformatics of long- range sequencing and mapping (Sedlazeck et al, 2018, Nature Reviews Genetics)
5	11-Sep	Wed	T2T, HPRC, pangenome		* The complete sequence of a human genome (Nurk et al, Science 2012) * Approaching complete genomes, transcriptomes and epi-omes with accurate long-read sequencing (Kovaka et al, 2023, Nature Methods * A draft human pangenome reference (Liao et al, 2023, Nature) * Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References (Taylor et al., 2024, Annual Review of Genomics and Human Genetics)
6	16-Sep	Mon	Read 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
7	18-Sep	Wed	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)
8	23-Sep	Mon	Human evolution	Assignment 3	* 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) * 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)
9	25-Sep	Wed	Intro to ML: PCA, Clustering, tSNE, UMAP, Decision Trees, NN		* 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
10	30-Sep	Mon	CNN + DeepVariant		* ImageNet Classification with Deep Convolutional Neural Networks (Krizhevsky et al., 2012, NIPS)
11	2-Oct	Wed	Functional Analysis 1: Annotation		* 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 * BEDTools: a flexible suite of utilities for comparing genomic features (Quinlan & Hall, 2010, Bioinformatics)
12	7-Oct	Mon	Functional Analysis 2: RNA-seq	Assignment 4	* 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)
13	9-Oct	Wed	Functional Analysis 3: Methyl-seq, Chip-seq, and Hi-C		* 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)
14	14-Oct	Mon	Functional Analysis 4: Regulatory States, ENCODE, GTEx, RoadMap	Project proposal	* 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)
15	16-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 (Lahnemann et al, Genome Biology, 2020)
16	21-Oct	Mon	Transformers	Assignment 5	* Attention is all you need (Vaswani et al. 2017, arXiv)
17	23-Oct	Wed	Transformers + Enformer		* Effective gene expression prediction from sequence by integrating long-range interactions (Avsec et al., 2021, Nature Methods) * Personal transcriptome variation is poorly explained by current genomic deep learning models (Huang et al., 2023, Nature Genetics) * Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings (Sasse et al., 2023, Nature Genetics)
18	28-Oct	Mon	Other applications of DL in Genomics	Prelim report assigned	* Deep Learning Sequence Models for Transcriptional Regulation (Sokolova et al., 2024, Annual Reviews of Genomics and Human Genetics) * AlphaFold (Jumper et al, 2021, Nature)
19	30-Oct	Wed	Midterm review
20	4-Nov	Mon	Midterm [In class exam]
21	6-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	11-Nov	Mon	Metagenomics	Prelim Report Due; Final Report Assigned	* Kraken: ultrafast metagenomic sequence classification using exact alignments (Wood and Salzberg, 2014, Genome Biology) * Chapter 12: Human Microbiome Analysis (Morgan and Huttenhower)
23	13-Nov	Wed	$${\color{red}\text{No class BIODATA24}}$$
24	18-Nov	Mon	Cancer Genomics		* 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)
25	20-Nov	Wed	In class project presentation
*	25-Nov	Mon	$${\color{red}\text{Thanksgiving Break}}$$
*	27-Nov	Wed	$${\color{red}\text{Thanksgiving Break}}$$
26	2-Dec	Mon	In class project presentation
27	4-Dec	Wed	In class project presentation
*	16-Dec	Mon	Final Report Due	Final Report Due