回顾和评估 ATAC-seq 和 CUT&Tag 数据的生物信息学分析策略。

IF 11.5 2区 生物学 Q1 GENETICS & HEREDITY
Siyuan Cheng,Benpeng Miao,Tiandao Li,Guoyan Zhao,Bo Zhang
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引用次数: 0

摘要

高效可靠的分析方法对研究表观遗传学至关重要。Tn5是最早发现的原核生物转座酶之一,具有很高的DNA结合和标记效率,在不同的基因组学和表观基因组学方案中被广泛采用,用于高通量探索基因组和表观基因组。在 Tn5 的基础上,开发了利用测序的转座酶染色质可及性分析(ATAC-seq)和目标下裂解和标记(CUT&Tag),以测量染色质可及性和检测 DNA 蛋白相互作用。这些方法可用于大量低输入水平的生物样本,如稀有组织、胚胎和分选的单细胞。然而,由于海量数据的产生持续快速增长,快速、正确地处理这些表观基因组数据已成为一个瓶颈。此外,不恰当的数据分析会产生有偏见或误导性的结论。因此,评估基于 Tn5 的 ATAC-seq 和 CUT&Tag 数据处理生物信息学工具的性能非常重要,其中许多工具主要是为分析染色质免疫沉淀后测序(ChIP-seq)数据而开发的。在这里,我们进行了一项全面的基准分析,评估了八种常用软件在处理 ATAC-seq 和 CUT&Tag 数据方面的性能。我们比较了窄型和宽型峰调用的灵敏度、特异性和峰宽分布。我们还测试了对照 IgG 输入对 CUT&Tag 数据分析的影响。最后,我们评估了常用于分析 CUT&Tag 数据的差异分析策略。我们的研究为选择生物信息学工具和推荐的分析策略提供了全面的指导,这些工具和策略已实施到 Docker/Singularity 映像中,以简化数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review and Evaluate the Bioinformatics Analysis Strategies of ATAC-seq and CUT&Tag Data.
Efficient and reliable profiling methods are essential to study epigenetics. Tn5, one of the first identified prokaryotic transposases with high DNA-binding and tagmentation efficiency, is widely adopted in different genomic and epigenomic protocols for high-throughputly exploring the genome and epigenome. Based on Tn5, the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and the Cleavage Under Targets and Tagmentation (CUT&Tag) were developed to measure chromatin accessibility and detect DNA-protein interactions. These methodologies can be applied to large amounts of biological samples with low-input levels, such as rare tissues, embryos, and sorted single cells. However, fast and proper processing of these epigenomic data has become a bottleneck because massive data production continues to increase quickly. Furthermore, inappropriate data analysis can generate biased or misleading conclusions. Therefore, it is essential to evaluate the performance of Tn5-based ATAC-seq and CUT&Tag data processing bioinformatics tools, many of which were developed mostly for analyzing chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Here, we conducted a comprehensive benchmarking analysis to evaluate the performance of eight popular software for processing ATAC-seq and CUT&Tag data. We compared the sensitivity, specificity, and peak width distribution for both narrow-type and broad-type peak calling. We also tested the influence of the availability of control IgG input in CUT&Tag data analysis. Finally, we evaluated the differential analysis strategies commonly used for analyzing the CUT&Tag data. Our study provided comprehensive guidance for selecting bioinformatics tools and recommended analysis strategies, which were implemented into Docker/Singularity images for streamlined data analysis.
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来源期刊
Genomics, Proteomics & Bioinformatics
Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
14.30
自引率
4.20%
发文量
844
审稿时长
61 days
期刊介绍: Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.
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