YODEL : Peak calling software for HITS - CLIP data
نویسنده
چکیده
YODEL is a peak calling software for analyzing RNA sequencing data generated by High-Throughput Sequencing of RNA isolated by Crosslinking Immunoprecipitation (HITS-CLIP; also known as CLIP-SEQ), a method to identify RNA-protein interactions genome-wide. We designed YODEL to analyze HITS-CLIP experiments, in which Argonaute proteins are immunoprecipitated, followed by sequencing of the associated RNA in order to identify bound microRNAs and their mRNA targets. The HITS-CLIP sequenced reads are mapped to the genome, and then read peaks are visualized where clustered sets of reads map to the same region. Several peak calling algorithms have been developed to define the boundaries of these peaks. In contrast to other peak callers for HITS-CLIP data, such as Piranha, YODEL does not map the starts of reads to fixed interval bins, but instead uses a heuristic approach to iteratively find the tallest point within a set clustered reads and examine bases upstream and downstream of that point until a peak has been determined. This allows the peak boundary to be defined more precisely than coordinates that are multiples of the bin size. Per-sample peak counts are also generated by YODEL, which quickly enables downstream differential representation analysis. YODEL is available at . https://github.com/LancePalmerStJude/YODEL/ Lance E. Palmer ( ) Corresponding author: [email protected] : Conceptualization, Formal Analysis, Software, Writing – Original Draft Preparation; : Funding Acquisition, Author roles: Palmer LE Weiss MJ Project Administration, Writing – Review & Editing; : Conceptualization, Supervision, Writing – Review & Editing Paralkar VR Competing interests: No competing interests were disclosed. Palmer LE, Weiss MJ and Paralkar VR. How to cite this article: YODEL: Peak calling software for HITS-CLIP data [version 1; referees: 2 2017, :1138 (doi: ) approved with reservations] F1000Research 6 10.12688/f1000research.11861.1 © 2017 Palmer LE . This is an open access article distributed under the terms of the , which Copyright: et al Creative Commons Attribution Licence permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. LEP was supported by the Cancer Center Support (CORE) Grant (CA021765). VRP was supported by the National Institute of Grant information: Diabetes and Digestive and Kidney Diseases (NIDDK) grant (K08 5K08DK102533). MJW was supported by the NIDDK grant (R01 DK092318). This work was also supported by ALSAC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 18 Jul 2017, :1138 (doi: ) First published: 6 10.12688/f1000research.11861.1 1 2
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