Advances in data processing and application of imaging transcriptomics

HU Ke; LIU Bing

doi:10.12122/j.issn.1674-4500.2022.05.27

Volume 45 Issue 5

Sep. 2022

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HU Ke, LIU Bing. Advances in data processing and application of imaging transcriptomics[J]. Journal of Molecular Imaging, 2022, 45(5): 767-773. doi: 10.12122/j.issn.1674-4500.2022.05.27

Citation:

HU Ke, LIU Bing. Advances in data processing and application of imaging transcriptomics[J]. Journal of Molecular Imaging, 2022, 45(5): 767-773. doi: 10.12122/j.issn.1674-4500.2022.05.27

HU Ke, LIU Bing. Advances in data processing and application of imaging transcriptomics[J]. Journal of Molecular Imaging, 2022, 45(5): 767-773. doi: 10.12122/j.issn.1674-4500.2022.05.27

Citation:

HU Ke, LIU Bing. Advances in data processing and application of imaging transcriptomics[J]. Journal of Molecular Imaging, 2022, 45(5): 767-773. doi: 10.12122/j.issn.1674-4500.2022.05.27

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Advances in data processing and application of imaging transcriptomics

doi: 10.12122/j.issn.1674-4500.2022.05.27

HU Ke^1
,,
LIU Bing^{2
,
,}

1.
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China

Funds:

National Natural Science Foundation of China 81771451

Received Date: 2022-07-07
Publish Date: 2022-09-20

Abstract

Abstract

With the advent of brain-wide transcriptomics data, i.e. brain-wide gene expression atlases such as the Allen human brain atlas, imaging transcriptomics has opened new opportunities for understanding the relationship between spatial variations on molecular scale of the brain and macroscopic neuroimaging phenotypes. A growing body of literature is demonstrating relationships between gene expression and different properties of brain structure and function. This article introduces the gene expression dataset widely used in the field of imaging transcriptomics, as well as the basic steps and the commonly used toolbox for transcriptomics data processing, and outlines the basic workflow and three kinds of analysis methods for associating gene expression data with image data. In recent years, imaging transcriptomics has been widely used to understand brain neurodevelopment and various neuropsychiatric disorders. However, the field is still nascent, and several methodological challenges must be overcome to ensure the robustness of the findings. As the filed develops and existing methodologies are refined, future studies can be combined with increasingly more comprehensive and precise transcriptional atlas data, which will offer a powerful and reliable framework for identifying the molecular correlates of disease-related brain changes observed in vivo.
- imaging transcriptomics,
- Allen human brain atlas,
- gene expression,
- neuroimaging,
- brain disorders

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References(79)

References

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Advances in data processing and application of imaging transcriptomics

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