TY - JOUR T1 - RNA-Seq Mapping and Detection of Gene Fusions with a Suffix Array Algorithm A1 - Sakarya, Onur A1 - Breu, Heinz A1 - Radovich, Milan A1 - Chen, Yongzhi A1 - Wang, Yulei N. A1 - Barbacioru, Catalin A1 - Utiramerur, Sowmi A1 - Whitley, Penn P. A1 - Brockman, Joel P. A1 - Vatta, Paolo A1 - Zhang, Zheng A1 - Popescu, Liviu A1 - Muller, Matthew W. A1 - Kudlingar, Vidya A1 - Garg, Nriti A1 - Li, Chieh-Yuan A1 - Kong, Benjamin S. A1 - Bodeau, John P. A1 - Nutter, Robert C. A1 - Gu, Jian A1 - Bramlett, Kelli S. A1 - Ichikawa, Jeffrey K. A1 - Hyland, Fiona C. A1 - Siddiqui, Asim S. Y1 - 2012/04/05 N2 - Author Summary Advances in sequencing technology are enabling detailed characterization of RNA transcripts from biological samples. The fundamental challenge of accurately mapping the reads on transcripts and gleaning biological meaning from the data remains. One class of transcripts, gene fusions, is particularly important in cancer. Some gene fusions are prominent markers in leukemia, prostate, and other cancers and putatively causative in certain tumor types. We present a set of new RNA-Seq analysis techniques to map reads, and count expression of genes, exons and splicing junctions, especially those that give evidence of gene fusions. These tools are available in a software package with a straightforward graphical user interface. Using this software, we called and validated several gene fusions in a breast cancer cell line. By testing the presence of these fusions in a larger population of tumor cell lines and clinical samples, we found that two of them were expressed recurrently. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 8 IS - 4 UR - https://doi.org/10.1371/journal.pcbi.1002464 SP - e1002464 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002464 ER -