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基于整合表观基因组和功能表征分析对多种人类细胞类型的调控活性进行注释

Integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types.

作者信息

Dincer Tevfik Umut, Ernst Jason

机构信息

Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA.

Department of Biological Chemistry, University of California, Los Angeles, CA, 90095, USA.

出版信息

bioRxiv. 2023 Jul 15:2023.07.14.549056. doi: 10.1101/2023.07.14.549056.

Abstract

We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces (1) ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and (2) ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.

摘要

我们引入了ChromActivity,这是一个通过整合多个表观基因组图谱和各种功能表征数据集来预测和注释全基因组调控活性的计算框架。ChromActivity基于可用的表观基因组数据,针对多种细胞类型生成与每个功能表征数据集相关的全基因组调控活性预测。然后,对于每种细胞类型,它会基于这些预测中的组合和空间模式生成(1)ChromScoreHMM基因组注释,并生成(2)总体预测调控活性的ChromScore轨迹。ChromActivity为跨多种细胞类型分析和解释人类调控基因组提供了一种资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a76/10369970/05921fd7e5e8/nihpp-2023.07.14.549056v1-f0001.jpg

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