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AnnoMiner is a new web-tool to integrate epigenetics, transcription factor occupancy and transcriptomics data to predict transcriptional regulators

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Meiler,  Arno
Pichlmair, Andreas / Innate Immunity, Max Planck Institute of Biochemistry, Max Planck Society;

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Weitkunat,  Manuela
Schnorrer, Frank / Muscle Dynamics, Max Planck Institute of Biochemistry, Max Planck Society;

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Schnorrer,  Frank
Schnorrer, Frank / Muscle Dynamics, Max Planck Institute of Biochemistry, Max Planck Society;

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Habermann,  Bianca H.
Habermann, Bianca / Computational Biology, Max Planck Institute of Biochemistry, Max Planck Society;

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引用

Meiler, A., Marchiano, F., Haering, M., Weitkunat, M., Schnorrer, F., & Habermann, B. H. (2021). AnnoMiner is a new web-tool to integrate epigenetics, transcription factor occupancy and transcriptomics data to predict transcriptional regulators. Scientific Reports, 11(1):. doi:10.1038/s41598-021-94805-1.


引用: https://hdl.handle.net/21.11116/0000-0009-465F-F
要旨
Gene expression regulation requires precise transcriptional programs, led by transcription factors in combination with epigenetic events. Recent advances in epigenomic and transcriptomic techniques provided insight into different gene regulation mechanisms. However, to date it remains challenging to understand how combinations of transcription factors together with epigenetic events control cell-type specific gene expression. We have developed the AnnoMiner web-server, an innovative and flexible tool to annotate and integrate epigenetic, and transcription factor occupancy data. First, AnnoMiner annotates user-provided peaks with gene features. Second, AnnoMiner can integrate genome binding data from two different transcriptional regulators together with gene features. Third, AnnoMiner offers to explore the transcriptional deregulation of genes nearby, or within a specified genomic region surrounding a user-provided peak. AnnoMiner's fourth function performs transcription factor or histone modification enrichment analysis for user-provided gene lists by utilizing hundreds of public, high-quality datasets from ENCODE for the model organisms human, mouse, Drosophila and C. elegans. Thus, AnnoMiner can predict transcriptional regulators for a studied process without the strict need for chromatin data from the same process. We compared AnnoMiner to existing tools and experimentally validated several transcriptional regulators predicted by AnnoMiner to indeed contribute to muscle morphogenesis in Drosophila. AnnoMiner is freely available at http://chimborazo.ibdm.univ-mrs.fr/AnnoMiner/.