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Updated: Jan 20, 2026

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
Published on: March 15, 2019
Racial Representation Disparity of Population-Level Genomic Sequencing Efforts
Isaac E Kim1, Indra Neil Sarkar1
1Center for Biomedical Informatics, Brown University, Providence, RI.
Abstract:
To develop personalized treatments for diseases, it is essential that they reflect the population of individuals that may be affected by a given disease. Amidst claims that there may be racial disparities in research populations, there have been no direct studies to explore this disparity in disease incidence and research projects that involve genomic sequencing. The precise relationship between underrepresentation of certain races in genomic sequencing studies and health outcomes relative to these races is unknown. Here, we examine the disparities in racial representation of national datasets pertaining to clinical data, mortality rates, and a major initiative involving genomic sequence analysis (The Cancer Genome Atlas [TCGA]). The results suggest that black Americans are underrepresented for most cancers in TCGA compared to clinical and mortality datasets, whereas Asian Americans are overrepresented. These findings accentuate the importance of targeted efforts to recruit representative patient populations into studies involving genomic sequencing.
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