CREDO: Highly confident disease-relevant A-to-I RNA-editing discovery in breast cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Woochang Hwang, Stefano Calza, Marco Silvestri, Yudi Pawitan, Youngjo Lee

ABSTRACT

Adenosine-to-Inosine (A-to-I) RNA editing is the most prevalent post-transcriptional modification of RNA molecules. Researchers have attempted to find reliable RNA editing using next generation sequencing (NGS) data. However, most of these attempts suffered from a high rate of false positives, and they did not consider the clinical relevance of the identified RNA editing, for example, in disease progression. We devised an effective RNA-editing discovery pipeline called CREDO, which includes novel statistical filtering modules based on integration of DNA- and RNA-seq data from matched tumor-normal tissues. CREDO was compared with three other RNA-editing discovery pipelines and found to give significantly fewer false positives. Application of CREDO to breast cancer data from the Cancer Genome Atlas (TCGA) project discovered highly confident RNA editing with clinical relevance to cancer progression in terms of patient survival. RNA-editing detection using DNA- and RNA-seq data from matched tumor-normal tissues should be more routinely performed as multiple omics data are becoming commonly available from each patient sample. We believe CREDO is an effective and reliable tool for this problem. More... »

PAGES

5064

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-41294-y

DOI

http://dx.doi.org/10.1038/s41598-019-41294-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112971087

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30911020


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50 schema:description Adenosine-to-Inosine (A-to-I) RNA editing is the most prevalent post-transcriptional modification of RNA molecules. Researchers have attempted to find reliable RNA editing using next generation sequencing (NGS) data. However, most of these attempts suffered from a high rate of false positives, and they did not consider the clinical relevance of the identified RNA editing, for example, in disease progression. We devised an effective RNA-editing discovery pipeline called CREDO, which includes novel statistical filtering modules based on integration of DNA- and RNA-seq data from matched tumor-normal tissues. CREDO was compared with three other RNA-editing discovery pipelines and found to give significantly fewer false positives. Application of CREDO to breast cancer data from the Cancer Genome Atlas (TCGA) project discovered highly confident RNA editing with clinical relevance to cancer progression in terms of patient survival. RNA-editing detection using DNA- and RNA-seq data from matched tumor-normal tissues should be more routinely performed as multiple omics data are becoming commonly available from each patient sample. We believe CREDO is an effective and reliable tool for this problem.
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