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Introduction to Genomic Data Visualization and Interpretation | Griffith Lab

Genomic Visualization and Interpretations

Introduction to Genomic Data Visualization and Interpretation

Welcome to the Genomic Data Visualization and Interpretation tutorial series. The goal of this tutorial is to provide students with the skills necessary to visualize and interpret ‘omic’ data in various forms. To accomplish this task we will be exploring a number of tools and resources available through the R programming language and via the web, providing background where appropriate. We recommend using the navigation links found at the bottom and top of all course topic pages however students can also browse topics on the course page or search for individual topics via the search page. Exercises and questions to reinforce concepts are interspersed throughout each course topic. By the end of this course students should:

  • Have a solid understanding of basic computational biology techniques for visualizing and interpreting genomic data
  • Be familiar with a variety of web resources (e.g., genome browsers and portals) to aid in the interpretation of omic data
  • Be able to use R graphical packages for data visualization (e.g., ggplot2, GenVisR) and interactive visualization (e.g., shiny)
  • Be able to perform, visualize, and interpret expression, differential expression and pathway analysis results
  • Be able to assess a variant’s biological and clinical significance (e.g., VEP, ClinVar, and CIViC)

Module 1 Lecture