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Calculating the spatial density of regulatory chromatin interactions using multi-modal datasets from the same cell line.


ABSTRACT: Here, we present a protocol for calculating the spatial density of regulatory chromatin interactions (SD-RCI) using Hi-C, ATAC-seq, and ChIP-seq datasets from the same cell line. We describe steps for selecting and preprocessing datasets, training and predicting a model to obtain regulatory chromatin interactions, and evaluating model performance. We then detail calculation of SD-RCI and visualization of the correlation between SD-RCI and gene expression. This protocol is applicable to Hi-C, ATAC-seq, and ChIP-seq data from the human cell line. For complete details on the use and execution of this protocol, please refer to Gong et al. (2023).1.

SUBMITTER: Gong H 

PROVIDER: S-EPMC10068612 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Calculating the spatial density of regulatory chromatin interactions using multi-modal datasets from the same cell line.

Gong Haiyan H   Li Minghong M   Ji Mengdie M   Zhang Xiaotong X   Yuan Zan Z   Zhang Sichen S   Yang Yi Y   Li Chun C   Chen Yang Y  

STAR protocols 20230330 2


Here, we present a protocol for calculating the spatial density of regulatory chromatin interactions (SD-RCI) using Hi-C, ATAC-seq, and ChIP-seq datasets from the same cell line. We describe steps for selecting and preprocessing datasets, training and predicting a model to obtain regulatory chromatin interactions, and evaluating model performance. We then detail calculation of SD-RCI and visualization of the correlation between SD-RCI and gene expression. This protocol is applicable to Hi-C, ATA  ...[more]

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