Research
Efficient count-based models improve power and robustness for large-scale single-cell eQTL mapping
Nature · By Zixuan Eleanor Zhang ·
The Brief
- The study presents jaxQTL, a count-based pseudobulk framework for single-cell eQTL mapping.
- When applied to OneK1K data, jaxQTL discovers more eGenes than existing methods.
- The source abstract describes the framework as efficient but is truncated, so run-time details are not confirmed here.
Why it matters
Single-cell eQTL studies depend on statistical methods that detect genetic effects on gene expression, and a method that finds more eGenes could improve power in large cell-type-resolved genetic studies.
Who’s affected
- statistical geneticists
- researchers running single-cell eQTL studies
- #single-cell
- #eqtl
- #genetics
- #pseudobulk
- #statistical methods
Nature Genetics, Published online: 10 November 2026; doi:10.1038/s41588-026-02830-5 This study presents jaxQTL, an efficient count-based pseudobulk single-cell eQTL mapping framework. When applied to OneK1K data, jaxQTL discovers more eGenes than existing methods while running…
Timeline
Published online in Nature Genetics (doi:10.1038/s41588-026-02830-5)
nature.com
Efficient count-based models improve power and robustness for large-scale single-cell eQTL mapping