HumanRetinaLRSData

Human long-read sequencing data of retinal organoids, 2D retinal ganglion cell cultures, and flow-through from EP1 and H9 cell lines.

Overview

This data package accompanies the study available here. Our research explores:

• Gene and isoform diversity across developmental time points of Retinal Organoid (RO) differentiation
• Gene and isoform expression in Retinal Ganglion Cells (RGCs) compared to other cell types (flow-through)
• Haplotype-resolved gene expression differences between RO stages, RGCs, and flow-through samples

Installation

# Install from Bioconductor (if applicable)
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("HumanRetinaLRSData")

Usage

Retinal Organoid Data

Access gene-level and isoform-level data across RO developmental stages:

library(HumanRetinaLRSData)

# Gene-level expression data
ro_genes <- ROGeneLevelData()

# Isoform-level expression data
ro_isoforms <- ROIsoformLevelData()

RGC and Flow-Through Data

Access gene-level and isoform-level data for RGCs and flow-through samples:

# Gene-level expression data
ftrgc_genes <- FTRGCGeneLevelData()

# Isoform-level expression data
ftrgc_isoforms <- FTRGCIsoformLevelData()

Allele-Specific Expression Data

Access haplotype-resolved gene counts:

# Haplotype-resolved gene counts matrix
ase_counts <- ASEGeneCounts()

Data Description

All data are provided as SummarizedExperiment objects (except ASE data, which is a counts matrix), making them compatible with standard Bioconductor workflows for analysis and visualization.

Citation

If you use this data package, please cite our associated study:

Keuthan CJ, Parthiban S, Chang Y-Y, Shan X, Chang X, Yan E, Cavalier S, Timp W, Hicks SC, Zack DJ (2025). Dynamic changes in mRNA isoform usage during human retinal development. bioRxiv. doi: 10.1101/2025.11.26.689062

Contact

For questions or issues, please open an issue on the GitHub repository.