Human Retina Atlas
A single cell atlas of the human retina that is composed of 2.5 million single cells from 48 donors has been generated by combining previously published and newly generated datasets. As a result, over 90 distinct cell types are identified based on the transcriptomics profile with the rarest cell type accounting forabout 0.01% of the cell population. In addition, open chromatin profiling has been generated for over 400K nuclei via single nuclei ATAC-seq, allowing systematic characterization of cis-regulatory elements for individualcell type. Integrative analysis reveals intriguing differences in the transcriptome, chromatin landscape, and gene regulatory network among cell class, subgroup, and type. In addition, changes in cell proportion, gene expression and chromatin openness have been observed between different gender and over age.
Single Cell Atlas of the Human RetinaCELLxGENE provides data collection for the Human Retina Cell Atlas (HRCA) with six datasets. It is suitable for exploring gene expression for either a single gene or a set of genes, as well as for analyzing the differential gene expression between cell clusters for various retinal cell types.
Single Cell Multiome Atlas of the Human RetinaUCSC Cell Browser provides specialized interfaces to explore multi-omic data of the Human Retina Cell Atlas (HRCA).
Single Cell Multiome Atlas of the Human Fetal RetinaTo provide a comprehensive view of the human fetal retina at the molecular level and investigate transcriptional regulatory mechanisms controlling the differentiation process, we profiled more than 300,000 single nuclei of the human fetal retina from 12 donors spanning post conception week 10 and 23 with Multiome RNA-seq and ATAC-seq. Please cite our article.
HCA DCPTwo parallel references were derived from single cell and single nuclei RNA-seq, respectively. Over 110 cell types in the human retina are identified, nearly doubling the number reported in previous studies. Integrative atlas with RNA and ATAC-seq, generating comprehensive gene regulatory landscape at single-cell resolution for the human retina.