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CICERO: a versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data
To discover driver fusions beyond canonical exon-to-exon chimeric transcripts, we develop CICERO, a local assembly-based algorithm that integrates RNA-seq read support with extensive annotation for candidate ranking. CICERO outperforms commonly used methods, achieving a 95% detection rate for 184 in...
Autores principales: | Tian, Liqing, Li, Yongjin, Edmonson, Michael N., Zhou, Xin, Newman, Scott, McLeod, Clay, Thrasher, Andrew, Liu, Yu, Tang, Bo, Rusch, Michael C., Easton, John, Ma, Jing, Davis, Eric, Trull, Austyn, Michael, J. Robert, Szlachta, Karol, Mullighan, Charles, Baker, Suzanne J., Downing, James R., Ellison, David W., Zhang, Jinghui |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325161/ https://www.ncbi.nlm.nih.gov/pubmed/32466770 http://dx.doi.org/10.1186/s13059-020-02043-x |
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