Literature DB >> 27897010

MAPPING NEURONAL CELL TYPES USING INTEGRATIVE MULTI-SPECIES MODELING OF HUMAN AND MOUSE SINGLE CELL RNA SEQUENCING.

Travis Johnson1, Zachary Abrams, Yan Zhang, Kun Huang.   

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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Year:  2017        PMID: 27897010      PMCID: PMC6956653          DOI: 10.1142/9789813207813_0055

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  20 in total

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Authors:  Amit Zeisel; Ana B Muñoz-Manchado; Simone Codeluppi; Peter Lönnerberg; Gioele La Manno; Anna Juréus; Sueli Marques; Hermany Munguba; Liqun He; Christer Betsholtz; Charlotte Rolny; Gonçalo Castelo-Branco; Jens Hjerling-Leffler; Sten Linnarsson
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3.  Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma.

Authors:  Anoop P Patel; Itay Tirosh; John J Trombetta; Alex K Shalek; Shawn M Gillespie; Hiroaki Wakimoto; Daniel P Cahill; Brian V Nahed; William T Curry; Robert L Martuza; David N Louis; Orit Rozenblatt-Rosen; Mario L Suvà; Aviv Regev; Bradley E Bernstein
Journal:  Science       Date:  2014-06-12       Impact factor: 47.728

4.  Genome-wide RNA-seq analysis of human and mouse platelet transcriptomes.

Authors:  Jesse W Rowley; Andrew J Oler; Neal D Tolley; Benjamin N Hunter; Elizabeth N Low; David A Nix; Christian C Yost; Guy A Zimmerman; Andrew S Weyrich
Journal:  Blood       Date:  2011-05-19       Impact factor: 22.113

5.  Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain.

Authors:  Blue B Lake; Rizi Ai; Gwendolyn E Kaeser; Neeraj S Salathia; Yun C Yung; Rui Liu; Andre Wildberg; Derek Gao; Ho-Lim Fung; Song Chen; Raakhee Vijayaraghavan; Julian Wong; Allison Chen; Xiaoyan Sheng; Fiona Kaper; Richard Shen; Mostafa Ronaghi; Jian-Bing Fan; Wei Wang; Jerold Chun; Kun Zhang
Journal:  Science       Date:  2016-06-24       Impact factor: 47.728

6.  Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types.

Authors:  Diego Adhemar Jaitin; Ephraim Kenigsberg; Hadas Keren-Shaul; Naama Elefant; Franziska Paul; Irina Zaretsky; Alexander Mildner; Nadav Cohen; Steffen Jung; Amos Tanay; Ido Amit
Journal:  Science       Date:  2014-02-14       Impact factor: 47.728

7.  Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.

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8.  Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE.

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Journal:  Nat Biotechnol       Date:  2011-10-02       Impact factor: 54.908

9.  Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations.

Authors:  Nicola K Wilson; David G Kent; Florian Buettner; Mona Shehata; Iain C Macaulay; Fernando J Calero-Nieto; Manuel Sánchez Castillo; Caroline A Oedekoven; Evangelia Diamanti; Reiner Schulte; Chris P Ponting; Thierry Voet; Carlos Caldas; John Stingl; Anthony R Green; Fabian J Theis; Berthold Göttgens
Journal:  Cell Stem Cell       Date:  2015-05-21       Impact factor: 24.633

10.  Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists.

Authors:  Da Wei Huang; Brad T Sherman; Richard A Lempicki
Journal:  Nucleic Acids Res       Date:  2008-11-25       Impact factor: 16.971

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  3 in total

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Authors:  Travis S Johnson; Tongxin Wang; Zhi Huang; Christina Y Yu; Yi Wu; Yatong Han; Yan Zhang; Kun Huang; Jie Zhang
Journal:  Bioinformatics       Date:  2019-11-01       Impact factor: 6.937

2.  BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes.

Authors:  Tongxin Wang; Travis S Johnson; Wei Shao; Zixiao Lu; Bryan R Helm; Jie Zhang; Kun Huang
Journal:  Genome Biol       Date:  2019-08-12       Impact factor: 13.583

3.  Spatial cell type composition in normal and Alzheimers human brains is revealed using integrated mouse and human single cell RNA sequencing.

Authors:  Travis S Johnson; Shunian Xiang; Bryan R Helm; Zachary B Abrams; Peter Neidecker; Raghu Machiraju; Yan Zhang; Kun Huang; Jie Zhang
Journal:  Sci Rep       Date:  2020-10-22       Impact factor: 4.379

  3 in total

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