The single-cell RNA-seq data generated in the study <b><i>Strategies for Arterial Grafts Optimization at Single Cell Level</i></b>

This dataset collection contains the human single-cell RNA-seq data generated in the study <b><i>Strategies for Arterial Grafts Optimization at Single Cell Level</i></b>.Coronary artery disease (CAD) is the leading cause of myocardial infarction and heart failure. Coronary artery bypass grafting (CABG) is the most effective way to treat CAD, especially in some high-risk conditions, such as severe lesions or in combination with other heart diseases. Common arterial grafts used in coronary artery bypass grafting include internal thoracic artery (ITA), radial artery (RA), and right gastroepiploic artery (RGA), among which ITA has the best clinical outcomes. Here, we performed single-cell RNA sequencing (scRNA-seq) to find optimization strategies for RA and RGA by using ITA as a reference.For each of the nine samples (RA1, RA2, RA3, ITA1, ITA2, ITA3, RGA1, RGA2, RGA3) collected in this study, the CellRanger output as gene expression matrices (both raw_feature_bc_matrix and filtered_feature_bc_matrix) are provided in both h5 format and mtx.gz format. CellRanger (version 5.0.1, 10x genomics) was used with default parameters to map all the samples’ scRNAseq data to the human reference genome (GRCh38) provided by 10x Genomics.