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Manorm2 用于定量比较 ChIP-seq 样本组。

MAnorm2 for quantitatively comparing groups of ChIP-seq samples.

机构信息

CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Genome Res. 2021 Jan;31(1):131-145. doi: 10.1101/gr.262675.120. Epub 2020 Nov 18.

Abstract

Eukaryotic gene transcription is regulated by a large cohort of chromatin-associated proteins, and inferring their differential binding sites between cellular contexts requires a rigorous comparison of the corresponding ChIP-seq data. We present MAnorm2, a new computational tool for quantitatively comparing groups of ChIP-seq samples. MAnorm2 uses a hierarchical strategy for normalization of ChIP-seq data and assesses within-group variability of ChIP-seq signals based on an empirical Bayes framework. In this framework, MAnorm2 allows for abundant differential ChIP-seq signals between groups of samples as well as very different global within-group variability between groups. Using a number of real ChIP-seq data sets, we observed that MAnorm2 clearly outperformed existing tools for differential ChIP-seq analysis, especially when the groups of samples being compared had distinct global within-group variability.

摘要

真核基因转录受一大类染色质相关蛋白调控,而要推断细胞环境下这些蛋白的差异结合位点,则需要对相应的 ChIP-seq 数据进行严格比较。我们提出了 MAnorm2,这是一种用于定量比较 ChIP-seq 样本组的新计算工具。MAnorm2 使用分层策略对 ChIP-seq 数据进行归一化,并基于经验贝叶斯框架评估 ChIP-seq 信号的组内变异性。在这个框架中,MAnorm2 允许在样本组之间存在大量的差异 ChIP-seq 信号,同时也允许组之间的组内全局变异性非常不同。使用多个真实的 ChIP-seq 数据集,我们观察到 MAnorm2 在差异 ChIP-seq 分析方面明显优于现有工具,尤其是在比较的样本组具有明显不同的组内全局变异性时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35b7/7849384/1349324bc179/131f01.jpg

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