{"title":"racoon_clip-a complete pipeline for single-nucleotide analyses of iCLIP and eCLIP data.","authors":"Melina Klostermann, Kathi Zarnack","doi":"10.1093/bioadv/vbae084","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>A vast variety of biological questions connected to RNA-binding proteins can be tackled with UV crosslinking and immunoprecipitation (CLIP) experiments. However, the processing and analysis of CLIP data are rather complex. Moreover, different types of CLIP experiments like iCLIP or eCLIP are often processed in different ways, reducing comparability between multiple experiments. Therefore, we aimed to build an easy-to-use computational tool for the processing of CLIP data that can be used for both iCLIP and eCLIP data, as well as data from other truncation-based CLIP methods.</p><p><strong>Results: </strong>Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.</p><p><strong>Availability and implementation: </strong>racoon_clip is implemented as a Snakemake-powered command line tool (Snakemake version ≥7.22, Python version ≥3.9). The latest release can be downloaded from GitHub (https://github.com/ZarnackGroup/racoon_clip/tree/main) and installed via pip. A detailed documentation, including installation, usage, and customization, can be found at https://racoon-clip.readthedocs.io/en/latest/. The example datasets can be downloaded from the Short Read Archive (SRA; iCLIP: SRR5646576, SRR5646577, SRR5646578) or the ENCODE Project (eCLIP: ENCSR202BFN).</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213630/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Motivation: A vast variety of biological questions connected to RNA-binding proteins can be tackled with UV crosslinking and immunoprecipitation (CLIP) experiments. However, the processing and analysis of CLIP data are rather complex. Moreover, different types of CLIP experiments like iCLIP or eCLIP are often processed in different ways, reducing comparability between multiple experiments. Therefore, we aimed to build an easy-to-use computational tool for the processing of CLIP data that can be used for both iCLIP and eCLIP data, as well as data from other truncation-based CLIP methods.
Results: Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.
Availability and implementation: racoon_clip is implemented as a Snakemake-powered command line tool (Snakemake version ≥7.22, Python version ≥3.9). The latest release can be downloaded from GitHub (https://github.com/ZarnackGroup/racoon_clip/tree/main) and installed via pip. A detailed documentation, including installation, usage, and customization, can be found at https://racoon-clip.readthedocs.io/en/latest/. The example datasets can be downloaded from the Short Read Archive (SRA; iCLIP: SRR5646576, SRR5646577, SRR5646578) or the ENCODE Project (eCLIP: ENCSR202BFN).