ArticleGigaScience2021
Building the mega single-cell transcriptome ocular meta-atlas.
Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Retinoic acid drives cell fate specification, maturation and retinal regionality in human retinal organoids.Nature communications · 2026Article
- Whole-Genome Landscape of Retinal Hemangioblastomas.Translational vision science & technology · 2026Article
- Integrative Learning of Disentangled Representations from Single-Cell RNA-Sequencing Datasets.Computational and structural biotechnology journal · 2026Article
- A comparative review of single-cell atlases: mapping cellular diversity across species and tissues.Cellular and molecular life sciences : CMLS · 2025Review
- Integrating single-cell RNA-seq datasets with substantial batch effects.BMC genomics · 2025Article
- Analysis of individual patient pathway coordination in a cross-species single-cell kidney atlas.Nature genetics · 2025Article
- Ocular Phenotyping of Knockout Mice Identifies Genes Associated With Late Adult Retinal Phenotypes.Investigative ophthalmology & visual science · 2025Article
- Systematic Ocular Phenotyping of Knockout Mouse Lines Identifies Genes Associated With Age-Related Corneal Dystrophies.Investigative ophthalmology & visual science · 2025Article
- Feature selection methods affect the performance of scRNA-seq data integration and querying.Nature methods · 2025Article
- Systematic ocular phenotyping of 8,707 knockout mouse lines identifies genes associated with abnormal corneal phenotypes.BMC genomics · 2025Article
- Single-cell sequencing in diabetic retinopathy: progress and prospects.Journal of translational medicine · 2025Review
- Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing.Nature methods · 2025Article
- Integrating single-cell RNA-seq datasets with substantial batch effects.bioRxiv : the preprint server for biology · 2024Article
- SCAN: Spatiotemporal Cloud Atlas for Neural cells.Nucleic acids research · 2024Article
- Lamin A upregulation reorganizes the genome during rod photoreceptor degeneration.Cell death & disease · 2023Article
- Single-cell reference mapping to construct and extend cell-type hierarchies.NAR genomics and bioinformatics · 2023Article
- PLAE Web App Enables Powerful Searching and Multiple Visualizations Across One Million Unified Single-Cell Ocular Transcriptomes.Translational vision science & technology · 2023Article
- Cell-cell interactome of the hematopoietic niche and its changes in acute myeloid leukemia.iScience · 2023Article
- An integrated cell atlas of the lung in health and disease.Nature medicine · 2023Article
- Spatial distribution of metabolites in the retina and its relevance to studies of metabolic retinal disorders.Metabolomics : Official journal of the Metabolomic Society · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe development of highly scalable single-cell transcriptome technology has resulted in the creation of thousands of datasets, >30 in the retina alone. Analyzing the transcriptomes between different projects is highly desirable because this would allow for better assessment of which biological effects are consistent across independent studies. However it is difficult to compare and contrast data across different projects because there are substantial batch effects from computational processing, single-cell technology utilized, and the natural biological variation. While many single-cell transcriptome-specific batch correction methods purport to remove the technical noise, it is difficult to ascertain which method functions best.
resultsWe developed a lightweight R package (scPOP, single-cell Pick Optimal Parameters) that brings in batch integration methods and uses a simple heuristic to balance batch merging and cell type/cluster purity. We use this package along with a Snakefile-based workflow system to demonstrate how to optimally merge 766,615 cells from 33 retina datsets and 3 species to create a massive ocular single-cell transcriptome meta-atlas.
conclusionsThis provides a model for how to efficiently create meta-atlases for tissues and cells of interest.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.