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Updated: Dec 25, 2025

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Humanizing Big Data: Recognizing the Human Aspect of Big Data.

Kathy Helzlsouer1, Daoud Meerzaman2, Stephen Taplin3

  • 1Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, United States.

Frontiers in Oncology
|April 2, 2020
PubMed
Summary
This summary is machine-generated.

Analyzing large volumes of genetic data presents challenges due to varied sources and technologies. This review focuses on the human aspect of genomic big data, emphasizing counseling and interpretation for individual impact.

Keywords:
big datacancer risk predictionclinical genetics/genomicsdata sharingdirect-to-consumer testingprecision medicinepredictive analytics

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Area of Science:

  • Genomics
  • Bioinformatics
  • Data Science

Background:

  • Big data, characterized by large volumes from diverse sources, is increasingly utilized for predictive analytics.
  • Genetic data, encompassing clinical testing, recreational testing (e.g., ancestry), and research studies, constitutes a significant type of big data.
  • The analysis of this genetic big data faces challenges including non-systematic data collection, diverse assay technologies, and variable variant classification/interpretation.

Purpose of the Study:

  • To evaluate the challenges associated with big data analysis in genomics.
  • To address the complexities of translating sophisticated genomic technologies to the individual level.
  • To emphasize the human element in genetic data, focusing on counseling, consent, and interpretation.

Main Methods:

  • Review of challenges in big data analysis.
  • Discussion of advanced genomic technologies like microarrays and next-generation sequencing.
  • Focus on the practical application and human considerations of genetic/genomic testing.

Main Results:

  • Identified challenges in analyzing massive genomic datasets.
  • Highlighted the need to consider the human aspect of genetic data sources.
  • Emphasized the importance of understanding assay limitations and interpretation.

Conclusions:

  • Translating genomic big data to individual impact requires addressing analytical challenges.
  • Adequate genetic counseling and informed consent are crucial in all genetic testing settings.
  • Understanding the strengths and limitations of genetic assays and their interpretation is vital for responsible application.