Intro to Applied Computational Genomics

Note: This Syllabus is subject to change.

Course Abstract

The goal of this course is to initiate wetlab biologists on the Ph.D. track to some basic skills in bioinformatics and computational genomics, and acquire basic computer literacy needed to perform analyses of next generation sequencing experiments. We will attend fundamental concepts in the analysis and interpretation of genomics data with a focus on single-cell and microbiome technologies, and explore the structure of key data types and their associated file formats. Twelve lectures is far to short a course to be considered comprehensive. Nonetheless we strive to empower students with basic skills to advocate for and analyze their own data.

Course Format

The course takes place over 12 weeks with 1.5 hour lectures on Fridays 10:30 AM - 12:00 PM. Most lectures are accompanied by either readings or some light homework or both. Any assignments must be completed on time for full credit, no exceptions. There is no final exam.

Expectations: Attendance, Homework & Grading

Late assignments will be given a maximum of 50% of full credit up to one lecture after the original due date. When homework is not assigned, points will be given for attendance. Readings are indicated on the syllabus. Each question set is worth 10 points and will be graded based on completeness. Links to lecture slides and readings will be provided in the syllabi below.

Attendance is required no exceptions. You may obtain permission ahead of time or with extenuating circumstances after the fact from the graduate school (email to Emma Yates Kassler). Homework assignments are required on time (see schedule below) regardless of attendance or for half credit one lecture late. Unexcused absences result in an incomplete grade.

After each lecture, a link will be posted to provide feedback. Attendance will be recorded by the completion of the "5 minute feedback". There will be three questions, with space for brief answers:

• What was the most important concept or take home message you learned from today's class?
• What concepts or topics from today's class do you not understand well enough?
• What suggestions do you have for improving or enhancing today's class?

Frequently asked questions or topics of confusion will be addressed in the subsequent lecture.

Lecture & assignment schedule:

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May 19th History of Bioinformatics (Hazelett)

Lecture topics:

• Introduction
• Course overview
• History of bioinformatics
• Introduction to Unix

Lecture slides:

Lecture 01

readings:

• Hagen NRG 2000
• Gauthier et al., 2018

feedback:

5 minute feedback

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May 26th Basic Unix Skills (Hazelett)

Lecture topics:

• More basic unix and tour the unix file system

Lecture slides:

Lecture 02 - starts slide 36

feedback:

5 minute feedback

Homework Assignment 1:

Due June 2nd

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June 2nd Version control with Git (Hazelett)

Lecture topics:

• What is reproducible science?
• Git Basics; creating and cloning a repo
• Adding, committing, and pull requests
• Reproducible science: the compileable manuscript (Guest Peter Nguyen)

Lecture slides:

Lecture 3

Readings:

• "A Quick Introduction to Version Control with Git and GitHub" Blischak et al., PLOS COMPBIO 2016
• "FAIRshake: Toolkit to Evaluate the FAIRness of Research Digital Resources" Clarke et al., Cell Systems 2020
• "A Beginner's Guide to Conducting Reproducible Research" Alston & Rick, Bulletin of the ESA 2021
• "A Manifesto for Reproducible Science" Munafo et al., Nature Human Behavior, 2017 -Optional-

Resources:

Coursera

feedback:

5 minute feedback

Homework Assignment 2:

Due June 9th

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June 9th Principle components analysis, heatmaps and clusterProfiler (Hazelett)

Lecture topics:

• What is PCA?
• Overview of hierarchical clustering and its pitfalls

Lecture slides:

Lecture 4

Readings:

Principal components analysis primer (2022)

the dendsort paper

Resources:

PCA explained

Step-by-step PCA (same author)

UMAP explained

feedback:

5 min feedback

Homework Assignment 3:

Due June 16th

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June 16th Genomics File Formats (Coetzee)

Lecture topics:

• Understanding NGS file formats
• Understanding NGS quality assessment

Lecture slides:

Lecture 04

feedback:

5 min feedback

Homework Assignment 4:

Due June 23rd

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June 23rd Working with data: Searching NGS File Formats and Using Genome Arithmetic (Coetzee)

Lecture topics:

• Search for characters or patterns in a text file using the grep command
• Learn to use bedtools to accomplish genome arithmetic.

Lecture slides:

Lecture 05

Lecture 05 markdown

feedback

5 min feedback

Homework Assignment 5:

Due June 30th

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June 30th Basics of Alignment and Quality Control (Coetzee)

Lecture topics:

• Understanding computational context of RNA-Seq.
• Learning to judge data for quality metrics of RNA-Seq.
• Quick differential expression analysis.

Lecture slides:

Lecture 06

Lecture 06 markdown

feedback

5 min feedback

Additional files

Differential Expression Page

Differential Expression Rmd

MultiQC Report

Homework Assignment 6:

Due July 7th

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July 7th scRNA-seq I: analysis of a single sample (Coetzee)

Lecture topics:

• Single cell analysis workflow
• Challenges of analysis
• Quality control

Lecture slides:

Lecture 08

Lecture 08 markdown

feedback

5 min feedback

Readings and websites:

• Orchestrating Single-Cell Analysis with Bioconductor (OSCA)
• Seurat
• Scanpy - single cell analysis with python
• scTransform
• Pearson Residuals for Normalization

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July 14th scRNA-seq II: analysis of a patient cohort (Coetzee)

Lecture topics:

• Data integration methods
• Cell type annotation
• Differential Expression

Lecture Slides:

Lecture 09

Lecture 09 markdown

feedback

5 min feedback

Readings and websites:

• Analysis File

• GPU - probabilistic models for single-cell omics

Homework Assignment 7:

Due July 28th

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July 21st BREAK

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July 28th Analysis of the Microbiome, part I (Vujkovic-Cvijin)

Lecture topics:

16S rRNA sequence data processing and analysis

Homework Assignment 8: Follow and complete the tutorial for dada2 prior to July 28th. Please also install the following R packages: vegan, phyloseq, lmerTest, lme4, ggplot2, dplyr, ape, reshape2

https://www.dropbox.com/scl/fo/eepu0rvg25n4ycml7livv/h?rlkey=yedzeixm8192u9wn9zgks3fux&dl=0

5 min feedback July 28

lecture slides

Microbiome Analysis Part 1 Homework, due August 15

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Aug 4th Analysis of the Microbiome, part II (Vujkovic-Cvijin)

5 min feedback Aug 4

lecture slides

Microbiome Analysis Part 2 Homework

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August 11th Visualization and Color Palettes (Coetzee)

Lecture topics:

• Color Perception
• Visual Accessibility
• Visualization of Data

Lecture slides:

Lecture 12

5 minute feedback

Overall Course Feedback

Helpful Books on the Subject:

• THE VISUAL DISPLAY OF QUANTITATIVE INFORMATION
• Data Visualization: A Practical Introduction

Schedule and Due Dates:

day	date	lecturer	topic	due
Friday	05/19	HAZELETT	History of Bioinformatics
Friday	05/26	HAZELETT	Basic Unix Skills
Friday	06/02	HAZELETT	Version Control & Git	Assignment 1
Friday	06/09	HAZELETT	PCA, heatmaps, clusterProfiler	Assignment 2
Friday	06/16	COETZEE	NGS File Formats	Assignment 3
Friday	06/23	COETZEE	Searching in files & Genome Arithmetic	Assignment 4
Friday	06/30	COETZEE	Advanced Search	Assignment 5
Friday	07/07	COETZEE	scRNA-seq I (single sample)	Assignment 6
Friday	07/14	COETZEE	scRNA-seq II (patient cohort)
Friday	07/21	BREAK		Assignment 8
Friday	07/28	VUJKOVIC-CVIJIN	Microbiome I	Assignment 7
Friday	08/04	VUJKOVIC-CVIJIN	Microbiome II	Assignmnet 8
Friday	08/11	COETZEE	Visualization & Color	Assignment 9