Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Namba et al develop a new pipeline called MuSTA to enable the efficient assembly of transcriptome from long-read sequencing data of breast cancer samples. This method enables the authors to discover subtype-specific isoforms, find that fusion transcript structures depend on their genomic context and...

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Auteurs principaux: Shinichi Namba, Toshihide Ueno, Shinya Kojima, Kenya Kobayashi, Katsushige Kawase, Yosuke Tanaka, Satoshi Inoue, Fumishi Kishigami, Shusuke Kawashima, Noriko Maeda, Tomoko Ogawa, Shoichi Hazama, Yosuke Togashi, Mizuo Ando, Yuichi Shiraishi, Hiroyuki Mano, Masahito Kawazu
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/fed8f30c93874058b219cc151c3f2be3
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