Method for establishing human brain gene expression space-time norm

Abstract

The invention discloses a method for establishing a human brain gene expression space-time norm. The method comprises the following steps: collecting brain space-time original data to obtain a gene standardized expression data set; constructing a two-dimensional space-time framework of a brain region and a development stage, and enabling all gene standardized expression data to correspond to the constructed space-time framework according to the brain region and development stage information to obtain a single-gene space-time expression mode; analyzing the obtained single-gene space-time expression matrix data by adopting a gene co-expression network analysis method to obtain a plurality of gene modules, and averaging the gene expression quantities of the gene modules to obtain a gene module space-time expression mode; analyzing the normal human nerve cell expression data, and performing the enrichment analysis of characteristic genes of nerve cells and the obtained gene modules to obtain a cell expression mode of the gene module. According to the method, all reference data sets are finally presented in the same two-dimensional space-time framework, so that the data sets from different sources are integrated, and researchers can intuitively supplement and compare the content of the space-time framework.

Description

technical field [0001] The invention relates to the technical field of human brain modeling, in particular to a method for establishing a spatiotemporal norm of human brain gene expression. Background technique [0002] The development of the human brain occurs over a long period of time, with extremely complex and precise regulation. From embryonic stage to adulthood and various stages of aging, the human brain undergoes long-term development, refinement and maturation, undergoing molecular, connection and structural changes. Provide insights into susceptibility to certain brain disorders such as neurodegenerative and psychiatric disorders by studying gene expression patterns in regions of normal brain function, developmental stages, and different neural cell types. [0003] A large amount of high-quality gene expression data of different types in the human brain is available. Considering the difference in gene length and sequencing depth in RNA-seq data analysis, it is a...

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Problems solved by technology

[0004] In order to solve the existing large amount of high-quality and different types of human brain gene expression data, the present invention optimizes the problem that existing database data resources are scattered and difficult to comprehensively utilize by integrating the normal human brain gene expression data of different develop

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