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How can I find high coverage whole genome sequencing (WGS) data?

Submitted by gaheens on

The GDC categorizes whole genome sequencing (WGS) coverage using the wgs_coverage property, which groups BAM files into four range buckets: 0x-10x, 10x-25x, 25x-150x, and 150x+. "High coverage" WGS in the GDC generally refers to alignments with a mean depth of 25x or greater — meaning, on average, each base in the genome is covered by at least 25 sequencing reads. This threshold reflects the minimum depth at which variant calling pipelines (SNV, indel, and structural variant) achieve reliable sensitivity and specificity for somatic mutation detection in cancer genomics.

Date: Monday, August 31, 2026
Time: 2:20 AM - 2:20 AM EDT
Location: Web Conference (See WebEx information below)
Speakers:
Dr. Bill Wysocki, Director of User Services, University of Chicago (UChicago)
Dr. Xin Zhou, Assistant Member, St. Jude Children's Research Hospital
Dr. Andriy Fedorov, Associate Professor, Harvard Medical School
Intended Audience

Researchers, bioinformaticians, data scientists, clinicians, and trainees interested in imaging and genomic data for cancer research are encouraged to attend. This webinar is especially valuable for investigators exploring histopathology and radiology images linked to cohorts with genomic characterizations, as well as those interested in AI and machine learning applications in oncology.

Abstract

Discover how the NCI Genomic Data Commons (GDC), in collaboration with the Imaging Data Commons (IDC), is advancing integrated cancer data exploration through the new IDC Image Viewer Tool available in the GDC Analysis Center. This webinar will provide a live demonstration of how researchers can access and visualize histopathology and radiology images associated with genomically characterized cohorts. Participants will learn how pathology and slide microscopy images are displayed using the IDC Slim Viewer, while radiology images and annotations are explored through the IDC Open Health Imaging Foundation (OHIF) Viewer. In addition to showcasing these image visualization tools, the session will highlight how integrated imaging and genomic datasets are being used to support artificial intelligence (AI) and machine learning research in cancer discovery and precision medicine. Attendees will also learn about GDC and IDC resources that facilitate AI tool development and multimodal data analysis.

Included Topics

Participants will gain practical insights into: 

  • Accessing and visualizing imaging data linked to genomically characterized cohorts using the IDC Image Viewer Tool
  • Navigating the IDC Slim Viewer to explore pathology and slide microscopy images and annotations 
  • Using the IDC OHIF Viewer to interact with radiology images and associated annotations 
  • Understanding how integrated genomic and imaging datasets support AI and machine learning applications in cancer research
  • Exploring GDC and IDC resources available for multimodal data analysis and AI tool development
Webex Information

Explore Cancer Imaging and Genomics with the New GDC Imaging Data Commons (IDC) Image Viewer Tool and IDC Viewers

  • Wednesday, September 9, 2026
  • 2:00 pm    |    Eastern Standard Time (New York, GMT-04:00)    |    1 hr
  • Meeting number (access code): 2312 377 9467 
  • Meeting password: Q3wbChZh@46 (73922494 when dialing from a phone or video system)

REGISTER/JOIN WEBEX MEETING.

IMPORTANT NOTICE: Please note that this Webex service allows audio and other information sent during the session to be recorded, which may be discoverable in a legal matter. By joining this session, you automatically consent to such recordings. If you do not consent to being recorded, discuss your concerns with the host or do not join the session.

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