title: Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives.
abstract: Gene fusions are important genomic events in human cancer because their fusion gene products can drive the development of cancer and thus are potential prognostic tools or therapeutic targets in anti-cancer treatment. Major advancements have been made in computational approaches for fusion gene discovery over the past 3 years due to improvements and widespread applications of high-throughput next generation sequencing (NGS) technologies. To identify fusions from NGS data, existing methods typically leverage the strengths of both sequencing technologies and computational strategies. In this article, we review the NGS and computational features of existing methods for fusion gene detection and suggest directions for future development.
authors.affiliation: Vanderbilt University, Nashville, TN 37235, USA.
authors.forename: Qingguo
authors.initials: Q
authors.lastname: Wang
authors.forename: Junfeng
authors.initials: J
authors.lastname: Xia
authors.forename: Peilin
authors.initials: P
authors.lastname: Jia
authors.forename: William
authors.initials: W
authors.lastname: Pao
authors.forename: Zhongming
authors.initials: Z
authors.lastname: Zhao
mesh_terms: D050939:Gene Fusion; D023281:Genomics / Q000379:methods* / Q000639:trends; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000235:genetics