HCL DGE Data

Single-cell analysis is a valuable tool to dissect cellular heterogeneity in complex systems. Yet, a systematic single-cell atlas has not been achieved for human beings. We used single-cell RNA sequencing to determine cell type composition of all major human organs and construct a basic scheme for the human cell landscape (HCL). We reveal a single-cell hierarchy for many tissues that has not been well characterized previously. We present a ‘‘single-cell HCL analysis’’ pipeline that accurately defines human cell types; and exemplify its utility in stem cell biology. Finally, we perform single-cell comparative analysis for human and mouse cell atlas to reveal the conserved genetic networks in the mammalian system.

HCL_Fig1_adata.h5ad: Use scanpy.api.read_h5ad to load AnnData. This AnnData stores the data used for HCL Figure 1.

HCL_Fig1_cell_Info: The information, which includes the cell names, samples, clusters, stages, batches, donors and cell types for cells of data used for HCL Figure 1.

cluster_markers_HCL&MCA1.1: The cell type annotation and marker genes for 102 HCL clusters of Fig1 and 104 MCA1.1 clusters of SFig.

dge_raw_data.tar: The raw digital expression matrix (dge) of more than 720,000 single cells sorted by tissues. The batch genes were not removed.

dge_rmbatch_data.tar: The batch gene removed dge of more than 700,000 primary single cells sorted by tissues. Some tissues are not included due to relatively strong batch effects. This dataset can be used to make global tissue tSNE plot and do cross-tissue analysis.

annotation_rmbatch_data.tar: The cell annotations, which include cluster ID, belonged tissues, age (gestational age for fetal tissue), clusters and cell types for each rmbatch dge data.

annotation_cluster_info: Modified cell type annotation of each cluster in accord with ClusterID in annotation_rmbatch_data.zip

MCA1.1_adata.h5ad: Use scanpy.api.read_h5ad to load AnnData. This AnnData stores the MCA1.1 data.

MCA1.1_cell_Info: The information, which includes the cell names, samples, clusters, stages, batches, donors and ce;; types for cells of MCA1.1 data.