title: MAPPING NEURONAL CELL TYPES USING INTEGRATIVE MULTI-SPECIES MODELING OF HUMAN AND MOUSE SINGLE CELL RNA SEQUENCING.
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.
authors.affiliation: Dept. Biomedical Informatics, Ohio State University, 250 Lincoln Tower, 1800 Cannon Dr. Columbus, 43210, Ohio, USA, Travis.Johnson@osumc.edu.
authors.forename: Travis
authors.initials: T
authors.lastname: Johnson
authors.forename: Zachary
authors.initials: Z
authors.lastname: Abrams
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhang
authors.forename: Kun
authors.initials: K
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000166:cytology / Q000378:metabolism; D019295:Computational Biology; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D006801:Humans; D051379:Mice; D008959:Models, Neurological; D005810:Multigene Family; D009474:Neurons / Q000145:classification* / Q000378:metabolism*; D017423:Sequence Analysis, RNA / Q000706:statistics & numerical data*; D013045:Species Specificity