NOV 12, 2015 9:00 AM PST

Introducing an ancestrally diverse whole genome data set for select cohort and control research applications

Speaker
  • Chief, Division of Medical Genomics, Inova Translational Medicine Institute, Associate Professor, Virginia Commonwealth University School of Medicine
    BIOGRAPHY

Abstract

Introduction and adoption of whole-genome sequencing has enabled new methods of investigation in the quest for answers in diagnostic odyssey cases as well as in the broader study of genetic diversity in affected and healthy populations. Ground breaking studies at the Inova Translational Medicine Institute (ITMI) have generated a data set of nearly 7,000 and growing fully sequenced genomes annotated with familial relationships, ancestral origin and clinical phenotypes. This data set has been the focus of a number of recent publications describing diverse applications including clinical diagnostic cases of children presenting with congenital anomalies and characterization of germline variation in cancer-susceptibility genes in a healthy population, as well as having provided the basis for an exploration of the utility of whole-genome sequencing for detection of newborn screening disorders.
Using these and other studies as examples, we will discuss the importance of having access to such an ancestrally diverse data set in understanding genetic variation and interpreting the likely clinical relevance of individual genomic variants.

Learning Objectives

  1. Appreciate the utility of whole-genome sequencing for diagnostic odyssey cases and cohort analyses
  2. Understand the value of an ancestrally diverse control data set 
  3. Apply allele frequency information in the evaluation of likely pathogenic variants for clinical significance

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NOV 12, 2015 9:00 AM PST

Introducing an ancestrally diverse whole genome data set for select cohort and control research applications


Specialty

Antibodies

Virology

Immunology

Dna Sequencing

Personalized Medicine

Clinical Diagnostics

Immunity

Cancer Diagnostics

Immunotherapy

Bioinformatics

Flow Cytometry

Immuno-Oncology

Gene Expression

Dna

Big Data

Geography

Europe100%

Registration Source

Website Visitors100%

Job Title

Student100%

Organization

Academic Institution100%


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