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A computational method for cell type-specific expression quantitative trait loci mapping using bulk RNA-seq data

Author

Listed:
  • Paul Little

    (Fred Hutchinson Cancer Center)

  • Si Liu

    (Fred Hutchinson Cancer Center)

  • Vasyl Zhabotynsky

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

  • Yun Li

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

  • Dan-Yu Lin

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

  • Wei Sun

    (Fred Hutchinson Cancer Center
    University of North Carolina at Chapel Hill
    University of Washington)

Abstract

Mapping cell type-specific gene expression quantitative trait loci (ct-eQTLs) is a powerful way to investigate the genetic basis of complex traits. A popular method for ct-eQTL mapping is to assess the interaction between the genotype of a genetic locus and the abundance of a specific cell type using a linear model. However, this approach requires transforming RNA-seq count data, which distorts the relation between gene expression and cell type proportions and results in reduced power and/or inflated type I error. To address this issue, we have developed a statistical method called CSeQTL that allows for ct-eQTL mapping using bulk RNA-seq count data while taking advantage of allele-specific expression. We validated the results of CSeQTL through simulations and real data analysis, comparing CSeQTL results to those obtained from purified bulk RNA-seq data or single cell RNA-seq data. Using our ct-eQTL findings, we were able to identify cell types relevant to 21 categories of human traits.

Suggested Citation

  • Paul Little & Si Liu & Vasyl Zhabotynsky & Yun Li & Dan-Yu Lin & Wei Sun, 2023. "A computational method for cell type-specific expression quantitative trait loci mapping using bulk RNA-seq data," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38795-w
    DOI: 10.1038/s41467-023-38795-w
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    References listed on IDEAS

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