Research highlights the need for diverse datasets in single-cell genomics to improve human health globally.
Single-cell genomics has transformed our ability to resolve cellular heterogeneity and map human biology at high resolution. However, most existing datasets are derived from a narrow subset of global genetic, environmental, and sociocultural contexts. This imbalance is far from trivial: it obscures context-specific effects, biases reference atlases, predictive tools, and foundation models, and constrains the global relevance of discoveries. We argue that diversity should be treated as a core study design principle, embedded from the outset in reference resources and atlases, metadata standards, analytical frameworks, and data governance. We outline actionable strategies that are essential to achieving population- and context-specific resources at this foundational stage, so that single-cell genomics can deliver robust biological inference and genuinely global benefits for human health.
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Shahin et al. (2026) studied this question.
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