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Course Description

A little over two decades since the first draft of the human genome sequence was published, high-throughput sequencing data is now routinely being generated at single cell level. These high-throughput data sets are being generated for multiple modalities, including transcriptomics, epigenomics, genomics, and proteomics. Significant advances have been made in the primary processing of these data sets that include mapping the data to reference genome and quantifying the data. However, the downstream analysis remains a major challenge, particularly in integrating data originating from multiple modalities.

Systematic integration of data originating from multiple modalities has the potential to decode novel cellular events that orchestrate gene regulation. Such integrative analyses can help elucidate molecular mechanisms that underlie the development or disease states of a cell or tissue. Here we look at strategies on how Transcriptomic, Genetic, and Epigenetic data sets can be integrated to decode the underlying biology of interest. 

What this course will not cover: This course in not intended to cover bioinformatics specific primary processing steps of sequencing data sets such as alignment, quantification etc. This course more focuses on  strategies for high level integration of disparate sequencing data sets with some programming in R involved.
 

Learner Outcomes

When you complete the course successfully, you will be able to:

  • Formulate integration strategies for data sets originating from two or more distinct modalities
  • Identify the different application areas of next generation sequencing technologies. 
  • Develop and implement integration strategies for data originating from single cell experiments. 

Microcredential(s)

This course applies toward the Bioinformatics Endeavor digital badge.

Textbook Information

There is no textbook for purchase required for this course.

Prerequisites

BIOF 521 or similar background in sequencing/omics. Please see course description for further details on background knowledge required for the course.

Refund
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Scholarship and Funding

Are you a self-funded student? FAES offers scholarship options. Click here for more information and to apply. 

Looking for resources to help you acquire funding for your continued education? Click here for our funding justification guide. 

Photo Release

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Section Title
Introduction to Omics and Data Integration
Type
Online Asynchronous
Dates
Mar 25, 2026 to May 12, 2026
Total Cost (Includes $75 non-refundable technology fee per course when applicable)
Eligible Discounts Can Be Applied at Checkout (2 Credits) $775.00
Potential Discount(s)
Available for Academic Credit
2 Credit(s)
Instructor(s)
  • Vejender Chaitankar
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