HCA Data Explorer

A multi-omics atlas of the human retina at single-cell resolution

Cell types in the human retina is highly heterogeneous with their abundance varies by several orders of magnitude. To decipher the complexity of gene expression and regulation of the human retinal cell types, we generated a multi-omics single-cell atlas of the adult human retina, including over 250K nuclei for single-nuclei RNA-seq and 150K nuclei for single-nuclei ATAC-seq. Over 60 cell subtypes have been identified based on their transcriptomic profiles, reaching a sensitivity of 0.01%. Integrative analysis of this single-cell multi-omics dataset identified gene regulatory elements across the genome for each cell subtype. In addition, when combined with other data modalities, such as eQTL, potential causal variants can be identified through fine mapping. Taken together, this new dataset represents the most comprehensive single-cell multi-omics profiling for the human retina that enables in-depth molecular characterization of most cell subtypes.

Rui ChenBaylor College of Medicineruichen@bcm.edu
Qingnan Liang (Experimental Scientist)1
Margaret DeAngelis (Principal Investigator)2
Xuesen Cheng (Experimental Scientist)1
Jun Wang (Experimental Scientist)1
Leah Owen (Experimental Scientist)3
Yumei Li (Experimental Scientist)1
Denise Morgan (Experimental Scientist)3
Ivana Kim (Experimental Scientist)3
Akbar Shakoor (Experimental Scientist)3
Albert Vitale (Experimental Scientist)3
Sangbae Kim (Experimental Scientist)1
Rui Chen (Principal Investigator)1
1Baylor College of Medicine
2Jacobs School of Medicine & Biomedical Sciences
3University of Utah

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Analysis Portals

UCSC Cell BrowserUCSC Cell Browser

Project Label



Homo sapiens

Sample Type


Anatomical Entity


Organ Part

4 organ parts

Selected Cell Types


Disease Status (Specimen)


Disease Status (Donor)


Development Stage

19 development stages

Library Construction Method

2 library construction methods

Nucleic Acid Source

single nucleus

Paired End


File Format

2 file formats

Cell Count Estimate


Donor Count

fastq387 file(s)pdf4 file(s)