ArticleNature communications2023
Projecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Machine Learning-Guided Stress Atlases Reveal Co-Expression Rewiring and Divergent Cellular Deployment of Abiotic Stress Programs in Rice and Wheat.International journal of molecular sciences · 2026Article
- sciLaMA: A Single-Cell Representation Learning Framework to Leverage Prior Knowledge from Large Language Models.bioRxiv : the preprint server for biology · 2025Article
- Integrated Single-Cell RNA Sequencing and Proteome-Wide Mendelian Randomization Identifies Therapeutic Targets for Psoriasis and Associated Complications.Psoriasis (Auckland, N.Z.) · 2025Article
- Distinctive physiology of molecularly identified medium spiny neurons in the macaque putamen.Cell reports · 2024Article
- scPair: Boosting single cell multimodal analysis by leveraging implicit feature selection and single cell atlases.Nature communications · 2024Article
- Integrated single cell-RNA sequencing and Mendelian randomization for ischemic stroke and metabolic syndrome.iScience · 2024Article
- Projecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection.Nature communications · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including identifying spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.
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Registered trials
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