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Single-Cell GWAS Integration

Definition
AI-generated

Single-cell GWAS integration denotes analytical approaches that combine genome-wide association results with single-cell transcriptomic (or multi-omic) reference data to infer which cell types, states, or programs are enriched for disease heritability or to prioritize genes at associated loci.

Topics
Single-cell analysis
Related
Gene Regulatory Network Inference Single-Cell Perturbation Genomics Spatial Transcriptomics

Why it matters in GWAS

It addresses the “which cell type?” question for polygenic and locus-level signal, moving from tissue-level bulk annotations toward cellular resolution when suitable atlases and methods exist.

Example usage

"Results report Single-Cell GWAS Integration with uncertainty estimates to support clinical and epidemiological interpretation."

Gene Regulatory Network Inference Single-Cell Perturbation Genomics Spatial Transcriptomics Colocalization Genome-Wide Association Study (GWAS) Human Cell Atlas Polygenic Risk Score (PRS) Single-Cell Expression Quantitative Trait Locus (sc-eQTL) Single-Cell Sequencing Transcriptome-Wide Association Study (TWAS)
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Dimitrov D, Schrod S, Rohbeck M, et al. (2026). Interpretation, extrapolation and perturbation of single cells. Nat Rev Genet. https://doi.org/10.1038/s41576-025-00920-4
  • Jia P, et al. (2022). scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies. Genome Biol.
  • Cuomo ASE, Nathan A, Raychaudhuri S, et al. (2023). Single-cell genomics meets human genetics. Nat Rev Genet. https://doi.org/10.1038/s41576-023-00599-5
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