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跨实验室的脑细胞转录组分析及其在批量组织数据解释中的应用。

Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data.

机构信息

Graduate Program in Bioinformatics, University of British Columbia, Vancouver V6T 1Z4, Canada.

Department of Psychiatry, University of British Columbia, Vancouver V6T 2A1, Canada.

出版信息

eNeuro. 2017 Nov 30;4(6). doi: 10.1523/ENEURO.0212-17.2017. eCollection 2017 Nov-Dec.

Abstract

Establishing the molecular diversity of cell types is crucial for the study of the nervous system. We compiled a cross-laboratory database of mouse brain cell type-specific transcriptomes from 36 major cell types from across the mammalian brain using rigorously curated published data from pooled cell type microarray and single-cell RNA-sequencing (RNA-seq) studies. We used these data to identify cell type-specific marker genes, discovering a substantial number of novel markers, many of which we validated using computational and experimental approaches. We further demonstrate that summarized expression of marker gene sets (MGSs) in bulk tissue data can be used to estimate the relative cell type abundance across samples. To facilitate use of this expanding resource, we provide a user-friendly web interface at www.neuroexpresso.org.

摘要

建立细胞类型的分子多样性对于神经系统的研究至关重要。我们使用严格编辑的来自汇集细胞类型微阵列和单细胞 RNA 测序(RNA-seq)研究的已发表数据,从哺乳动物大脑的 36 种主要细胞类型中编译了一个跨实验室的小鼠大脑细胞类型特异性转录组数据库。我们使用这些数据来识别细胞类型特异性标记基因,发现了大量新的标记基因,其中许多我们使用计算和实验方法进行了验证。我们还进一步证明,在批量组织数据中总结标记基因集(MGS)的表达可以用于估计样本间的相对细胞类型丰度。为了方便使用这个不断扩展的资源,我们在 www.neuroexpresso.org 上提供了一个用户友好的网络界面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/5707795/25cc898519cf/enu006172455r001.jpg

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