MORA and EnsembleTFpredictor: An ensemble approach to reveal functional transcription factor regulatory networks.

MORA and EnsembleTFpredictor: An ensemble approach to reveal functional transcription factor regulatory networks.
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DOI:
10.1371/journal.pone.0294724
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发表时间:
2023
期刊:
影响因子:
3.7
通讯作者:
--
中科院分区:
综合性期刊3区
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--
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我们的研究旨在确定控制一组共表达或共调节基因表达的生物学相关转录因子(TFs)。我们开发了一个完全自动化的流水线,Motif Over Representation Analysis (MORA),用于检测任何查询序列中已知TF结合Motif的富集程度。使用数百个差异表达基因集和来自已知tf的ChIP-seq数据集进行评估,MORA的表现优于或可与其他五种tf预测工具相媲美。此外,我们开发了EnsembleTFpredictor来利用多个tf预测工具的功能,提供按预测置信度排序的功能tf列表。当应用于测试数据集时,EnsembleTFpredictor不仅识别了目标TF,还揭示了相应生物系统中已知的许多与目标TF合作的TF。MORA和EnsembleTFpredictor已经在两篇出版物中使用,展示了它们在指导实验设计和揭示新的生物学见解方面的力量。
Our study aimed to identify biologically relevant transcription factors (TFs) that control the expression of a set of co-expressed or co-regulated genes. We developed a fully automated pipeline, Motif Over Representation Analysis (MORA), to detect enrichment of known TF binding motifs in any query sequences. MORA performed better than or comparable to five other TF-prediction tools as evaluated using hundreds of differentially expressed gene sets and ChIP-seq datasets derived from known TFs. Additionally, we developed EnsembleTFpredictor to harness the power of multiple TF-prediction tools to provide a list of functional TFs ranked by prediction confidence. When applied to the test datasets, EnsembleTFpredictor not only identified the target TF but also revealed many TFs known to cooperate with the target TF in the corresponding biological systems. MORA and EnsembleTFpredictor have been used in two publications, demonstrating their power in guiding experimental design and in revealing novel biological insights.
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