Soibam Benjamin
Department of Computer Science and Engineering Technology, University of Houston-Downtown, Houston, TX 77002, United States.
Bioinform Adv. 2023 Sep 14;3(1):vbad126. doi: 10.1093/bioadv/vbad126. eCollection 2023.
Analysis of network motifs is crucial to studying the robustness, stability, and functions of complex networks. Genome organization can be viewed as a biological network that consists of interactions between different chromatin regions. These interacting regions are also marked by epigenetic or chromatin states which can contribute to the overall organization of the chromatin and proper genome function. Therefore, it is crucial to integrate the chromatin states of the nodes when performing motif analysis in chromatin interaction networks. Even though there has been increasing production of chromatin interaction and genome-wide epigenetic modification data, there is a lack of publicly available tools to extract chromatin state-marked motifs from genome organization data.
We develop a Python tool, ChromNetMotif, offering an easy-to-use command line interface to extract chromatin-state-marked motifs from a chromatin interaction network. The tool can extract occurrences, frequencies, and statistical enrichment of the chromatin state-marked motifs. Visualization files are also generated which allow the user to interpret the motifs easily. ChromNetMotif also allows the user to leverage the features of a multicore processor environment to reduce computation time for larger networks. The output files generated can be used to perform further downstream analysis. ChromNetMotif aims to serve as an important tool to comprehend the interplay between epigenetics and genome organization.
ChromNetMotif is available at https://github.com/lncRNAAddict/ChromNetworkMotif.
网络模体分析对于研究复杂网络的稳健性、稳定性和功能至关重要。基因组组织可被视为一个由不同染色质区域之间的相互作用组成的生物网络。这些相互作用区域还由表观遗传或染色质状态标记，这些状态有助于染色质的整体组织和适当的基因组功能。因此，在染色质相互作用网络中进行模体分析时，整合节点的染色质状态至关重要。尽管染色质相互作用和全基因组表观遗传修饰数据的产量不断增加，但缺乏从基因组组织数据中提取染色质状态标记模体的公开可用工具。
我们开发了一个Python工具ChromNetMotif，它提供了一个易于使用的命令行界面，用于从染色质相互作用网络中提取染色质状态标记的模体。该工具可以提取染色质状态标记模体的出现次数、频率和统计富集情况。还会生成可视化文件，方便用户解释这些模体。ChromNetMotif还允许用户利用多核处理器环境的特性来减少大型网络的计算时间。生成的输出文件可用于进行进一步的下游分析。ChromNetMotif旨在成为理解表观遗传学与基因组组织之间相互作用的重要工具。
ChromNetMotif可在https://github.com/lncRNAAddict/ChromNetworkMotif上获取。
