scRNA-seq data of: A novel in vitro tubular model to recapitulate features of distal airways: the bronchioid

We provide a .Rds file of an annotated Seurat Object of scRNA-seq data of two bronchioid models derived from distinct donors after 21days of culture using 10x genomics 3' v3 chemistry. Raw data was processed using CellRanger v7.1.0. Cells were filtered based on detected UMIs (>2000) and fraction of mitochondrial counts (<10%).Metadata annotations contain:- Patient -> patient information for every cell (patient1 or patient2)- nCount_RNA -> UMI counts per cell- nFeature_RNA -> genes detected per cell- percent.mt -> mitochondrial count fraction per cell- seurat_clusters -> unsupervised clustering results using Louvain algorithm with resolution = 0.5- Manual.Annotation -> Cell types annotated based on marker gene expression- Celltypist.prediction -> Cell types predicted with CellTypist Python package- Celltypist.prediction.ari -> Cell types predicted with CellTypist Python package, with harmonized names for comparison with manual annotation

本数据集提供一份经注释的Seurat对象（Seurat Object）的.Rds格式文件，该对象包含两名不同供体来源的类支气管模型在采用10x Genomics 3' v3化学试剂体系培养21天后的单细胞RNA测序（scRNA-seq）数据。原始测序数据采用CellRanger v7.1.0进行处理。研究人员根据检测到的UMI（唯一分子标识符，Unique Molecular Identifier）计数（>2000）及线粒体基因计数占比（<10%）对细胞进行筛选。元数据注释信息如下：
- Patient：对应每个细胞的供体信息（患者1或患者2）
- nCount_RNA：每个细胞的UMI计数
- nFeature_RNA：每个细胞检测到的基因数量
- percent.mt：每个细胞的线粒体基因计数占比
- seurat_clusters：使用Louvain算法（分辨率参数设为0.5）得到的无监督聚类结果
- Manual.Annotation：基于标记基因表达注释得到的细胞类型
- Celltypist.prediction：使用CellTypist Python工具包预测得到的细胞类型
- Celltypist.prediction.ari：使用CellTypist Python工具包预测并经名称统一化处理的细胞类型，用于与手动注释结果进行比对