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Metadensity: a background-aware python pipeline for summarizing CLIP signals on various transcriptomic sites

MOTIVATION: Cross-linking and immunoprecipitation (CLIP) is a technology to map the binding sites of RNA-binding proteins (RBPs). The region where an RBP binds within RNA is often indicative of its molecular function in RNA processing. As an example, the binding sites of splicing factors are found w...

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Detalles Bibliográficos
Autores principales: Her, Hsuan-Lin, Boyle, Evan, Yeo, Gene W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653213/
https://www.ncbi.nlm.nih.gov/pubmed/36388152
http://dx.doi.org/10.1093/bioadv/vbac083
Descripción
Sumario:MOTIVATION: Cross-linking and immunoprecipitation (CLIP) is a technology to map the binding sites of RNA-binding proteins (RBPs). The region where an RBP binds within RNA is often indicative of its molecular function in RNA processing. As an example, the binding sites of splicing factors are found within or proximal to alternatively spliced exons. To better reveal the function of RBPs, we developed a tool to visualize the distribution of CLIP signals around various transcript features. RESULTS: Here, we present Metadensity (https://github.com/YeoLab/Metadensity), a software that allows users to generate metagene plots. Metadensity allows users to input features such as branchpoints and preserves the near-nucleotide resolution of CLIP technologies by not scaling the features by length. Metadensity normalizes immunoprecipitated libraries with background controls, such as size-matched inputs, then windowing in various user-defined features. Finally, the signals are averaged across a provided set of transcripts. AVAILABILITY AND IMPLEMENTATION: Metadensity is available at https://github.com/YeoLab/Metadensity, with example notebooks at https://metadensity.readthedocs.io/en/latest/tutorial.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.