STAR Chimeric Post for rapid detection of circular RNA and fusion transcripts
Nicholas K Akers1, Eric E Schadt1, Bojan Losic1
1Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Bioinformatics (Oxford, England)
|February 24, 2018
Summary
STARChip is a new software for detecting circular RNAs (circRNAs) and gene fusions from chimeric RNA alignments. It offers rapid, efficient, and scalable analysis for large medical datasets, improving upon existing tools.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Chimeric RNA alignments, including chromosomal fusions and circular RNAs (circRNAs), are biologically significant, particularly in cancer.
- Existing software for fusion discovery and circRNA detection suffers from high false positive rates, long runtimes, and limited capabilities, hindering large-scale analysis.
Purpose of the Study:
- To introduce STAR Chimeric Post (STARChip), a novel software package for processing chimeric RNA alignments.
- To enable rapid, efficient, and scalable detection and quantification of circRNAs and high-precision gene fusions.
Main Methods:
- STARChip processes chimeric alignments generated by the STAR aligner.
- The software annotates and quantifies both circRNAs and fusion events.
Main Results:
- STARChip provides annotated circRNA and high-precision fusion detection.
- The software is rapid, efficient, and scalable, suitable for high-dimensional medical omics datasets.
Conclusions:
- STARChip addresses the limitations of existing tools for analyzing chimeric RNA.
- This novel software facilitates robust and scalable discovery of circRNAs and gene fusions in large datasets.
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