Mapping neuronal cell types using integrative multi-species modeling of human and mouse single cell rna sequencing

Travis Johnson, Zachary Abrams, Yan Zhang, Kun Huang

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

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.

Original languageEnglish
Pages (from-to)599-610
Number of pages12
JournalPacific Symposium on Biocomputing
Volume0
Issue number212679
DOIs
StatePublished - 2017
Event22nd Pacific Symposium on Biocomputing, PSB 2017 - Kohala Coast, United States
Duration: Jan 4 2017Jan 8 2017

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