Single Cell CPTAC RCC

These data include a subset of single-cell samples from the CPTAC Renal Cell Carcinoma data processed using the following steps: Loom files were read into R and converted into SingleCellExperiment objects. Ensembl gene ID's were matched to HGNC symbols, chromosome name, starting position, and ending position via Biomart using the scater R package. Size factors were computed using the scran R package. UMAP dimensions were computed using the scater R package. Probes without matching HGNC symbols were removed. Where duplicate HGNC symbols were present, the gene with the maximum normalized range was retained. Cell types were inferred using the scMRMA R package. Cells with less than or equal to 1,000 features were removed. Cells with mitochondrial reads greater than or equal to 50% were removed. Expression data for podocytes and macrophages were saved separately for each sample. For podocytes and macrophages for each sample, expression data were projected onto the first 100 principal components using the irlba R package. The results are available from CPTAC_RCC_PCA.zip. For macrophages for each sample, a differentiation trajectory was estimated using the monocle3 R package, and plots were colored by combined expression of the M0 markers CSF1R, CD14, CD68, and CD11B, the M1 markers CD86, MARC0, CXCL9, CXCL10, CXCL11, NOS2, SOCS1, and CD64, and the M2 markers TGM2, CD23, ARG1, CCL22, CD163, and CD206 (from PMC8268869). Pseudotime starting points were annotated in monocle3 using visual inspection of plots. Only samples in which a visible trajectory from M0 -> M1 -> M2 was evident using these markers were retained. For podocytes for each sample, a differentiation trajectory was estimated using the monocle3 R package, and plots were colored by combined expression of the dedifferentiation markers DACH1 (from PMC5908116) and PTPRO (from PMID9639039. Pseudotime starting points were annotated in monocle3 using visual inspection of plots. Only samples in which a visible trajectory of dedifferentiation was evident using these markers were retained. These pseudotime assignments and the macrophage assignments are available from CPTAC_RCC_pseudotime_all_cells.zip. For podocytes and macrophages for each sample, 10-fold cross-validation matrices for expression, PCA, and pseudotime were generated across 5 random splits, for a total of 50 files per cell type, per sample. These files are available from CPTAC_RCC_expression_all_cells.zip. Expression data were subset to include 63 randomly-selected podocytes and 63 randomly-selected macrophages to ensure balanced data. These expression data are available from CPTAC_RCC_expression.zip. Pseudotimes were also subset and are available in CPTAC_RCC_pseudotime.zip. Expression data were projected onto the first 100 principal components. These data are available from CPTAC_RCC_expression_dimReduced.zip.本数据集包含从CPTAC肾细胞癌（Renal Cell Carcinoma）数据中选取的单细胞样本子集，其预处理流程如下： 将Loom文件导入R语言环境，并转换为SingleCellExperiment对象。 通过scater R包调用Biomart数据库，将Ensembl基因ID（Ensembl gene ID）匹配至HGNC符号（HGNC symbols）、染色体名称、起始位置与终止位置。 使用scran R包计算测序大小因子。 借助scater R包计算UMAP降维坐标。 移除未匹配到HGNC符号的探针。 若存在重复的HGNC符号，则保留归一化极差最大的基因。 通过scMRMA R包推断细胞类型。 移除基因特征数≤1000的细胞。 移除线粒体reads占比≥50%的细胞。 为每个样本分别保存足细胞（podocytes）与巨噬细胞（macrophages）的表达矩阵。 针对每个样本的足细胞与巨噬细胞，使用irlba R包将表达矩阵投影至前100个主成分，相关结果可从CPTAC_RCC_PCA.zip获取。 针对每个样本的巨噬细胞，借助monocle3 R包推断其分化轨迹，并以M0型标志物CSF1R、CD14、CD68、CD11B，M1型标志物CD86、MARC0、CXCL9、CXCL10、CXCL11、NOS2、SOCS1、CD64，以及M2型标志物TGM2、CD23、ARG1、CCL22、CD163、CD206（文献来源：PMC8268869）的联合表达量对可视化结果上色。通过可视化检视轨迹图注释伪时间起始点，仅保留可通过上述标志物观测到M0→M1→M2分化轨迹的样本。 针对每个样本的足细胞，借助monocle3 R包推断其去分化轨迹，并以去分化标志物DACH1（文献来源：PMC5908116）与PTPRO（文献来源：PMID9639039）的联合表达量对可视化结果上色。通过可视化检视轨迹图注释伪时间起始点，仅保留可通过上述标志物观测到去分化轨迹的样本。上述伪时间标注结果与巨噬细胞标注结果可从CPTAC_RCC_pseudotime_all_cells.zip获取。 针对每个样本的足细胞与巨噬细胞，通过5次随机划分生成表达矩阵、PCA结果与伪时间的10折交叉验证矩阵，每个细胞类型、每个样本共生成50个文件，相关文件可从CPTAC_RCC_expression_all_cells.zip获取。 为保证数据均衡，从表达矩阵中随机选取63个足细胞与63个巨噬细胞进行子集采样。该子集表达数据可从CPTAC_RCC_expression.zip获取，对应的伪时间数据同样进行了子集采样，可从CPTAC_RCC_pseudotime.zip获取。 将上述子集表达矩阵投影至前100个主成分，相关降维后的数据可从CPTAC_RCC_expression_dimReduced.zip获取。