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Bioinformatics
Article . 2018
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SPRINT: an SNP-free toolkit for identifying RNA editing sites

Authors: Zhang, Feng; Lu, Yulan; Yan, Sijia; Xing, Qinghe; Tian, Weidong;

SPRINT: an SNP-free toolkit for identifying RNA editing sites

Abstract

Abstract Motivation RNA editing generates post-transcriptional sequence alterations. Detection of RNA editing sites (RESs) typically requires the filtering of SNVs called from RNA-seq data using an SNP database, an obstacle that is difficult to overcome for most organisms. Results Here, we present a novel method named SPRINT that identifies RESs without the need to filter out SNPs. SPRINT also integrates the detection of hyper RESs from remapped reads, and has been fully automated to any RNA-seq data with reference genome sequence available. We have rigorously validated SPRINT’s effectiveness in detecting RESs using RNA-seq data of samples in which genes encoding RNA editing enzymes are knock down or over-expressed, and have also demonstrated its superiority over current methods. We have applied SPRINT to investigate RNA editing across tissues and species, and also in the development of mouse embryonic central nervous system. A web resource (http://sprint.tianlab.cn) of RESs identified by SPRINT has been constructed. Availability and implementation The software and related data are available at http://sprint.tianlab.cn. Supplementary information Supplementary data are available at Bioinformatics online.

Related Organizations
Keywords

Mice, Genome, Sequence Analysis, RNA, Databases, Genetic, Animals, RNA, Reproducibility of Results, RNA Editing, Original Papers, Software

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
83
Top 1%
Top 10%
Top 10%
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