ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2017
MAPPING NEURONAL CELL TYPES USING INTEGRATIVE MULTI-SPECIES MODELING OF HUMAN AND MOUSE SINGLE CELL RNA SEQUENCING.
Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Spatial cell type composition in normal and Alzheimers human brains is revealed using integrated mouse and human single cell RNA sequencing.Scientific reports · 2020Article
- LAmbDA: label ambiguous domain adaptation dataset integration reduces batch effects and improves subtype detection.Bioinformatics (Oxford, England) · 2019Article
- BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes.Genome biology · 2019Article
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4 authors.
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Abstract
Mouse brain transcriptomic studies are important in the understanding of the structural heterogeneity in the brain. However, it is not well understood how cell types in the mouse brain relate to human brain cell types on a cellular level. We propose that it is possible with single cell granularity to find concordant genes between mouse and human and that these genes can be used to separate cell types across species. We show that a set of concordant genes can be algorithmically derived from a combination of human and mouse single cell sequencing data. Using this gene set, we show that similar cell types shared between mouse and human cluster together. Furthermore we find that previously unclassified human cells can be mapped to the glial/vascular cell type by integrating mouse cell type expression profiles.
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Registered trials
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