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MOSim:批量和单细胞多层调控网络模拟器。

MOSim: bulk and single-cell multilayer regulatory network simulator.

作者信息

Monzó Carolina, Aguerralde-Martin Maider, Martínez-Mira Carlos, Arzalluz-Luque Ángeles, Conesa Ana, Tarazona Sonia

机构信息

Genomics of Gene Expression Lab, Institute for Integrative Systems Biology, Spanish National Research Council (CSIC-UV), C/ Catedràtic Agustín Escardino Benlloch, Paterna 46980, Spain.

Applied Statistics, Operational Research and Quality Department, Universitat Politècnica de València, Camí de Vera s/n, València 46022, Spain.

出版信息

Brief Bioinform. 2025 Mar 4;26(2). doi: 10.1093/bib/bbaf110.

Abstract

As multi-omics sequencing technologies advance, the need for simulation tools capable of generating realistic and diverse (bulk and single-cell) multi-omics datasets for method testing and benchmarking becomes increasingly important. We present MOSim, an R package that simulates both bulk (via mosim function) and single-cell (via sc_mosim function) multi-omics data. The mosim function generates bulk transcriptomics data (RNA-seq) and additional regulatory omics layers (ATAC-seq, miRNA-seq, ChIP-seq, Methyl-seq, and transcription factors), while sc_mosim simulates single-cell transcriptomics data (scRNA-seq) with scATAC-seq and transcription factors as regulatory layers. The tool supports various experimental designs, including simulation of gene co-expression patterns, biological replicates, and differential expression between conditions. MOSim enables users to generate quantification matrices for each simulated omics data type, capturing the heterogeneity and complexity of bulk and single-cell multi-omics datasets. Furthermore, MOSim provides differentially abundant features within each omics layer and elucidates the active regulatory relationships between regulatory omics and gene expression data at both bulk and single-cell levels. By leveraging MOSim, researchers will be able to generate realistic and customizable bulk and single-cell multi-omics datasets to benchmark and validate analytical methods specifically designed for the integrative analysis of diverse regulatory omics data.

摘要

随着多组学测序技术的发展,对于能够生成逼真且多样(批量和单细胞)多组学数据集以进行方法测试和基准测试的模拟工具的需求变得越来越重要。我们展示了MOSim,一个R包,它可以模拟批量(通过mosim函数)和单细胞(通过sc_mosim函数)多组学数据。mosim函数生成批量转录组学数据(RNA测序)和额外的调控组学层(ATAC测序、miRNA测序、ChIP测序、甲基化测序和转录因子),而sc_mosim以scATAC测序和转录因子作为调控层来模拟单细胞转录组学数据(scRNA测序)。该工具支持各种实验设计,包括基因共表达模式的模拟、生物学重复以及不同条件之间的差异表达。MOSim使用户能够为每种模拟的组学数据类型生成定量矩阵,捕捉批量和单细胞多组学数据集的异质性和复杂性。此外,MOSim在每个组学层中提供差异丰富的特征,并阐明批量和单细胞水平上调控组学与基因表达数据之间活跃的调控关系。通过利用MOSim,研究人员将能够生成逼真且可定制的批量和单细胞多组学数据集,以对专门为不同调控组学数据的综合分析设计的分析方法进行基准测试和验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5420/11926980/c0535a80bc42/bbaf110f1.jpg

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