Syllabus§

General Information§

Title:Genome Analysis Workshop
Course Number:MOLB 7621
Cross listings:STBB 7621, MICB 7621
Semester:Spring 2017
Homepage:http://molb7621.github.io/workshop
Instructor:Jay Hesselberth
Organization:University of Colorado School of Medicine
Address:Department of Biochemistry and Molecular Genetics RC1 South 10104 Aurora CO 80045
Copyright:2014,2015 Jay R. Hesselberth All Rights Reserved.
Last updated:Apr 18, 2017

PDF Content§

The course content is available as a combined PDF: PDF Download

Instructor Information§

Instructor Email
Jay Hesselberth jay.hesselberth@gmail.com
Kent Riemondy kent.riemondy@ucdenver.edu
Mandy Richer mandylricher@gmail.com
Laura White laura.k.white@ucdenver.edu

Schedule§

  • Lecture: Tue & Thurs, 1:00 - 3:00 PM.
  • TA office hours: until 3:30 PM after lectures and on Fridays at 2 PM in the RNA Bioscience Initiative informatics office space (RC1S rm.9101 behind the glass walls).

See specific dates.

Location§

Ed 2 North (P28-CTL-2201AB)

Course Description§

The Genome Analysis Workshop is a hands-on tutorial of skills needed to process large genomics data sets and visualize their results. The class is taught from the standpoint of biologist with practical goals (e.g. to interpret the results of a sequencing-based experiment and gain biologically meaningful insight).

We focus on working in the Linux environment, with emphasis on Linux command-line tools, Python programming and the R statistical computing environment. We use publicly available next-generation DNA sequencing data from the ENCODE project to illustrate standard approaches for manipulating sequencing data, aligning sequences to a reference genome, generating coverage plots and displaying them in the UCSC Genome Browser. We will cover specific analyses used in ENCODE project including ChIP-seq, DNase I footprinting, mRNA-seq and genome sequencing to identify single nucleotide and structural variants.

Course Credits§

This is a 3 credit course.

Texts and Reading Materials§

  1. Required: A Quick Guide to Organizing Computational Biology Projects PubMed ID 19649301
  2. Required: Command Line Crash Course http://cli.learncodethehardway.org/book/
  3. Required: Learn Python the Hard Way, http://learnpythonthehardway.org/book/
  4. Suggested: ggplot2: Elegant Graphics for Data Analysis http://ggplot2.org/book/

Course Objectives§

  • Learn to manipulate large sequencing data sets with Linux command line tools and Python programming.
  • Learn to manipulate and visualize data with the R statistical computing environment.
  • Learn workflows for ENCODE experiments including ChIP-seq, mRNA-seq and variant detection.

Canvas§

The course has a Canvas page [1] where announcements are made and problem sets are uploaded. You need to login to see Announcements and Problem Sets.

[1]https://ucdenver.instructure.com/courses/325063

Assessment§

Progress of individual students will be assessed during the daily exercise session, weekly problem sets, as well as a final project.

Grading Criteria§

  • 50% participation
  • 40% problem sets (10 sets, 4% each)
  • 10% final project

Specific Dates / Material to be Covered§

Class number Date Topic Problem Set
Class 1 2017 Jan 26 Thurs Introduction to VM, Linux and the shell  
Class 2 2017 Jan 31 Tues Linux / Utilities  
Class 3 2017 Feb 2 Thurs Linux / Utilities  
Class 4 2017 Feb 7 Tues grep and awk  
Class 5 2017 Feb 9 Thurs BEDTools PS1 due (2017 Feb 9 5:00 PM MDT)
Class 6 2017 Feb 14 Tues Analysis vignette: ChIP-seq PS2 due (2017 Feb 14 5:00 PM MDT)
Class 7 2017 Feb 16 Thurs BEDTools  
Class 8 2017 Feb 21 Tues Genome Browser PS3 due (2017 Feb 21 5:00 PM MDT)
Class 9 2017 Feb 23 Thurs R Data & Plotting  
Class 10 2017 Feb 28 Tues R Data & Plotting ** No Problem Set **
Class 11 2017 Mar 2 Thurs R Data & Plotting  
Class 12 2017 Mar 7 Tues R Data & Plotting PS4 due (2017 Mar 7 5:00 PM MDT)
Class 13 2017 Mar 9 Thurs R Data & Plotting  
Class 14 2017 Mar 14 Tues R Data & Plotting PS5 due (2017 Mar 14 5:00 PM MDT)
Class 15 2017 Mar 16 Thurs Python  
Class 16 2017 Mar 30 Thurs Python  
  ** No Class Mar 20-24 ** ** Spring Break **  
Class 17 2017 Apr 4 Tues Python  
Class 18 2017 Apr 6 Thurs Python PS6 due (2017 Apr 6 5:00 PM MDT)
Class 19 2017 Apr 11 Tues Python  
Class 20 2017 Apr 13 Thurs Python PS7 due (2017 Apr 13 5:00 PM MDT)
Class 21 2017 Apr 18 Tues mRNA-seq  
Class 22 2017 Apr 25 Tues mRNA-seq PS8 due (TBD)
Class 23 2017 Apr 27 Thurs Exome analysis  
Class 24 2017 May 2 Tues Exome analysis PS9 due (TBD)
Class 25 2017 May 4 Thurs Final Projects  
Class 26 2017 May 9 Tues Final Projects