Exploratory experiment designed to discover new patterns targeting C1QA, C1QC, SPI1 in human atherosclerotic plaque samples. Primary outcome: Identification of C1Q-related hub genes
Single-cell RNA sequencing analysis was performed on human atherosclerotic plaque samples to identify cell clusters and complement C1Q-related differentially expressed genes. The analysis identified 24 cell clusters and 12 cell types from the scRNA-seq dataset (GSE159677). Seven C1Q-associated differentially expressed genes were identified in both the scRNA-seq and bulk RNA-seq datasets. Machine learning algorithms including GBM, LASSO, and XGBoost were used to select C1QA and C1QC as hub genes from the seven DEGs. The study also identified SPI1 as a potential transcription factor regulating these hub genes in human atherosclerotic plaques.
scRNA-seq data analysis using GEO dataset GSE159677, machine learning algorithms (GBM, LASSO, XGBoost), ssGSEA pathway scoring, ROC analysis
Identification of C1Q-related genes associated with atherosclerotic plaques
Satisfactory diagnostic accuracy in training and validation cohorts
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