The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases, providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages. Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity. However, our knowledge of brain transcriptional characteristics remains very limited. With the immense efforts to generate high-quality brain transcriptome atlases, new computational approaches to analyze these high-dimensional multivariate data are greatly needed. In this review, we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field, which would aid in making new discoveries in brain development and disorders.
大脑是人类最神秘的器官，始终吸引着无数研究者的目光。近10年来，高通量测序技术的快速发展产生了大量有价值的脑转录组图谱，为系统研究大脑各个脑区和不同发育阶段的基因表达特征提供了巨大的机遇。最近的研究表明，基因转录是解释大脑复杂性的分子机制的关键。然而，我们对大脑中整体基因转录调控规律的了解仍然非常有限。与此同时，海量脑转录组图谱数据的生成，对数据的存储，分析方法等都提出了更高的要求。本文综述了现有的公共脑转录组数据集，并概述了脑转录组常用的计算分析方法。神经科学大数据和生物信息计算方法的高效结合，将有助于我们在脑发育和神经系统疾病方面有更多的新发现。





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