Krahasoni metodat

	Analiza e eQTL me qeliza individuale	Analiza e asociacionit gjenetik specifik për tipin qelizor GWAS me një qelizë
Fusha	Bioinformatikë	Bioinformatikë
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	2020	2019–2022 (rapid emergence with large-scale scRNA-seq atlases)
Krijuesi	Cuomo et al.; Kim-Hellmuth et al. (pioneering sc-eQTL frameworks, 2020)	Multiple groups (Price lab, De Jager lab, others); scDRS framework by Zhang et al. 2022
Lloji	Statistical genomics pipeline	Integrative genomic analysis pipeline
Burimi themelues	Cuomo, A. S. E., et al. (2020). Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression. Nature Communications, 11(1), 810.	Zhang, M. J., Hou, K., Dey, K. K., Sakaue, S., Jagadeesh, K. A., Weinand, K., ... & Price, A. L. (2022). Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data. Nature Genetics, 54(8), 1224-1234.
Emërtime të tjera	sc-eQTL analysis, single-cell eQTL mapping, scRNA-seq eQTL, cell-type-specific eQTL	sc-GWAS, single-cell GWAS integration, cell-type-specific GWAS, single-cell genetic association analysis
Të lidhura	6	6
Përmbledhja	Single-cell eQTL analysis identifies genetic variants (eQTLs) that regulate gene expression in a cell-type-specific manner by jointly analysing single-cell RNA-seq profiles and donor genotype data. Unlike bulk eQTL methods, it resolves regulatory effects that are diluted or masked when cell types are mixed, enabling discovery of variants whose effects are confined to particular cell states or developmental stages.	Single-cell GWAS is an integrative bioinformatics pipeline that maps genome-wide association study (GWAS) signals onto single-cell transcriptomic landscapes to identify which cell types and individual cells carry disproportionate genetic risk for a disease or trait. By leveraging single-cell RNA-seq atlases alongside GWAS summary statistics, it moves beyond tissue-level associations to reveal the precise cellular contexts in which disease-associated genetic variants exert their effects.