SPA

SPA maps GWAS summary statistics to single-cell RNA sequencing (scRNA-seq) expression profiles to annotate cell type–phenotype associations for complex diseases and traits.

Key Features:

• Cross Annotation Framework: Integrates scRNA-seq expression profiles with GWAS summary statistics to construct a cell type–phenotype association landscape linking over 20,000 single-cell clusters with 997 complex phenotypes.
• Cell-Type Specificity and Pleiotropy Analysis: Quantifies cell-type specificity and pleiotropy, reporting that >90% of phenotypes are moderately selective for a limited number of cell types while <10% of cell types show strong pleiotropic effects across ~100 phenotypes.
• Identification of Pleiotropy Blocks: Detects three distinct cell type–phenotype mutual pleiotropy blocks within the association landscape.
• Application to Human Disease Genetics: Applies the cross-annotation framework to explain phenomena such as T cell biased lymphopenia and to identify supporting genes associated with severe COVID-19.

Scientific Applications:

• Mapping cellular basis of complex traits: Enables assignment of genetic associations from GWAS to specific cell types using scRNA-seq data.
• Investigating immune-related phenotypes: Supports analysis of T cell biased lymphopenia by linking phenotype associations to immune cell clusters.
• Prioritizing candidate genes in disease: Identifies genes supporting severe COVID-19 susceptibility by integrating GWAS signals with single-cell expression patterns.

Methodology:

Performs cross-annotation by combining scRNA-seq expression profiles with GWAS summary statistics, linking >20,000 single-cell clusters to 997 phenotypes, quantifying cell-type specificity and pleiotropy, and identifying three mutual pleiotropy blocks.