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MESIA:用于精确峰调用的多表观基因组样本集成方法。

MESIA: multi-epigenome sample integration approach for precise peak calling.

机构信息

Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea.

Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea.

出版信息

Sci Rep. 2023 Nov 27;13(1):20859. doi: 10.1038/s41598-023-47948-2.

Abstract

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the most widely used method for measuring chromatin accessibility. Researchers have included multi-sample replication in ATAC-seq experimental designs. In epigenomic analysis, researchers should measure subtle changes in the peak by considering the read depth of individual samples. It is important to determine whether the peaks of each replication have an integrative meaning for the region of interest observed during multi-sample integration. We developed multi-epigenome sample integration approach for precise peak calling (MESIA), which integrates replication with high representativeness and reproducibility in multi-sample replication and determines the optimal peak. After identifying the reproducibility between all replications, our method integrated multiple samples determined as representative replicates. MESIA detected 6.06 times more peaks, and the value of the peaks was 1.32 times higher than the previously used method. MESIA is a shell-script-based open-source code that provides researchers involved in the epigenome with comprehensive insights.

摘要

转座酶可及染色质测序(ATAC-seq)分析是目前应用最广泛的检测染色质可及性的方法。研究人员在 ATAC-seq 实验设计中纳入了多样本重复实验。在表观基因组分析中,研究人员应该通过考虑单个样本的读取深度来测量峰的细微变化。重要的是要确定每个重复的峰是否对多样本整合过程中观察到的感兴趣区域具有综合意义。我们开发了用于精确峰调用的多表观基因组样本整合方法(MESIA),该方法在多样本重复中整合了具有高代表性和可重复性的复制,并确定了最优峰。在确定所有重复之间的再现性之后,我们的方法整合了多个被确定为代表性重复的样本。MESIA 检测到的峰数量增加了 6.06 倍,峰的值比之前使用的方法高 1.32 倍。MESIA 是一个基于 shell 脚本的开源代码,为从事表观基因组学研究的人员提供了全面的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b60/10681995/ec7f2ac70087/41598_2023_47948_Fig1_HTML.jpg

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