Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data.
Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data.
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DOI：
10.1523/eneuro.0212-17.2017
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发表时间：
2017-11
期刊：
影响因子：
3.4
通讯作者：
Pavlidis P
中科院分区：
文献类型：
--
作者：
Mancarci BO;Toker L;Tripathy SJ;Li B;Rocco B;Sibille E;Pavlidis P
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。我们使用来自汇集的细胞类型微阵列和单细胞RNA测序（RNA-seq）研究的严格策划的已发表数据，从哺乳动物大脑的36种主要细胞类型中编译了小鼠脑细胞类型特异性转录组的跨实验室数据库。我们使用这些数据来识别细胞类型特异性标记基因，发现了大量的新标记，其中许多我们使用计算和实验方法进行了验证。我们进一步证明，标记基因集（MGS）在大量组织数据中的汇总表达可用于估计样品间的相对细胞类型丰度。为了方便使用这一不断扩大的资源，我们提供了一个用户友好的网络界面，网址是www.neuroexpresso.org。
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.