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Updated: Aug 21, 2025

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
Metadensity: a background-aware python pipeline for summarizing CLIP signals on various transcriptomic sites
Hsuan-Lin Her1,2, Evan Boyle2, Gene W Yeo1,2,3,4
1Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA.
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.

