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

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Carolina Monzó, Maider Aguerralde-Martin, Carlos Martínez-Mira, Ángeles Arzalluz-Luque, Ana Conesa, Sonia Tarazona
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引用次数: 0

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.

MOSim:批量和单细胞多层调节网络模拟器。
随着多组学测序技术的进步,对能够生成真实和多样化(批量和单细胞)多组学数据集的模拟工具的需求变得越来越重要,用于方法测试和基准测试。我们介绍了MOSim,一个R包,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功能生成大量转录组学数据(RNA-seq)和额外的调节组学层(ATAC-seq, miRNA-seq, ChIP-seq, Methyl-seq和转录因子),而sc_mosim则以scATAC-seq和转录因子作为调节层模拟单细胞转录组学数据(scRNA-seq)。该工具支持各种实验设计,包括模拟基因共表达模式、生物复制和不同条件下的差异表达。MOSim使用户能够为每种模拟组学数据类型生成量化矩阵,捕获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了差异丰富的特征,并阐明了调节组学和基因表达数据在大量和单细胞水平上的积极调节关系。通过利用MOSim,研究人员将能够生成现实和可定制的批量和单细胞多组学数据集,以基准测试和验证专门为综合分析各种调节组学数据而设计的分析方法。
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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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