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Gene Expression Clustering in GDC 2.0

Date: Monday, July 15, 2024
Time: 2:00 PM - 3:00 PM EDT
Location: Web Conference (See WebEx information below)
Speakers:
Dr. Bill Wysocki, Director of User Services, University of Chicago (UChicago)
Intended Audience

This webinar is designed for researchers looking to explore gene expression clustering features within the newly launched NCI Genomic Data Commons (GDC) 2.0 platform. It is intended for anyone interested in analyzing gene expression data in the context of cancer, regardless of their previous experience in genomics. Additionally, the webinar caters to bioinformatics developers who wish to utilize GDC programmatic interfaces for gene expression clustering.

Abstract

The GDC Gene Expression Clustering tool, available in GDC 2.0, is a web-based application for performing sample clustering by selecting a specific set of genes and visualizing the results as a heatmap of a z-score transformed matrix. This webinar will demonstrate how to use the tool for clustering samples based on genes associated with specific disease types and conduct interactive analyses. It will also provide an overview of the GDC Application Programming Interface (API) endpoint for gene expression clustering. Participants will have the opportunity to ask questions to GDC experts and offer feedback on GDC 2.0.

Included Topics
  • Build custom cohorts for specific cancer disease types using the Cohort Builder 
  • Utilize the Gene Expression Clustering Tool to cluster samples based on a selected set of genes associated with specific cancer types 
  • Conduct interactive analysis of the Gene Expression Clustering heatmap by modifying gene groups and incorporating clinical variables 
  • Obtain an overview of the GDC API endpoint for gene expression clustering 
  • Answer user questions and gather feedback
Webex Information

Gene Expression Clustering in GDC 2.0

  • Monday, July 15, 2023
  • 2:00 pm    |    Eastern Standard Time (New York, GMT-04:00)    |    1 hr
  • Meeting number (access code): 2316 572 3513
  • Meeting password: Q7epeaY6s*5 (77373296 from phones and video systems)

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