Identifying genetic variants that influence the abundance of cell states in single-cell data
Laurie Rumker,
Saori Sakaue,
Yakir Reshef
et al.
Abstract:Introductory ParagraphTo understand genetic mechanisms driving disease, it is essential but difficult to map how risk alleles affect the composition of cells present in the body. Single-cell profiling quantifies granular information about tissues, but variant-associated cell states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce GeNA (Genotype-Neighborhood Associations), a statistical tool to identify cell state abundance quantitative trait loci (c… Show more
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