Integrative Omics 

SB 920
Tuesdays/Fridays 2-3:30PM
3-5 credits
Course Director
Kelly Ruggles (
Daniel Depledge (
Teaching Assistant: 
Menghan Liu 
Office Hours: Tuesdays 1:00-2:00PM SB 920
Course overview
The primary goal of this course is to train biomedical graduate students to work collaboratively towards a common interdisciplinary research goal through the analysis of a complex multimodal ‘omics data set to answer novel scientific questions. To address this goal, we require both a diverse student team and an interesting and high-quality data set. To address the latter, an original data set of interest will be chosen for each academic year. 
Raw data will be available prior to the start of the semester and students will be responsible for all downstream analysis and biological interpretation (with guidance from appropriate faculty).   A major objective of the course is to complete the data analysis and finalize a collaborative draft summarizing the results, with figures and writing done collectively by the students.  Students will be graded on their analytic and writing contributions and collaborative efforts and judged by both the course director and an external faculty committee. 
Course Assessment
100% of grade will be determined by projects and participation

Spring 2019 Dataset: Herpes simplex virus (HSV) is an important human pathogen which established lifelong latency in peripheral neurons, periodically reactivating to cause fresh disease. While initially thought to encode just 80 genes and a handful of microRNAs, recent studies have suggested far greater transcriptional complexity that results from alternative transcription initiation, alternative splicing, alternative polyadenylation, and read-through transcription. The major aim of this work is to integrate diverse RNA sequencing and proteomic datasets and produce a new updated annotation of the HSV-1 genome that will inform new biological explorations and interpretations.

Week 1: Overview & Data Types

February 5: Introducing Herpes Simplex Virus Type 1 (Angus Wilson)

February 8: Data types (Dan)

Week 2: Data Overview
February 12: QC, trimming, and sequence read alignment (Dan)

February 15: Data integration strategies (Kelly)

Week 3: Data Analysis Proposal
February 19: Data Analysis Proposal Group 1 
February 22: Data Analysis Proposal Group 2

Week 4, 5 & 6: Data processing 
February 26: Defining transcript boundaries (Dan)
March 1: Open meeting
March 5: Motif Discovery (Dan)
March 8: Open meeting
March 12: Elucidating patterns of splicing (Kelly)
March 15: Open meeting
** March 18-22 Spring Break **

Week 7: External Committee Assessment I
March 26: Group 1
March 29: Group 2

Week 8: Data processing
April 2: Interrogating proteomics data (Kelly
April 5: Open meeting

Week 9: Data Interpretation
April 9: Filtering noise (Kelly)
April 12: Open meeting
April 16: Imputing coding potential and function
April 19: Open meeting

Week 11-12: Data Summary
April 23: Open meeting
April 26: Open meeting
April 30: Open meeting
May 3: Open meeting

Week 13: External Committee Assessment II
May 7: Groups 1 & 2 (10 min presentations + 2 min questions)