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FusionAI, a DNA-sequence-based deep learning protocol reduces the false positives of human fusion gene prediction

Even though there were many tool developments of fusion gene prediction from NGS data, too many false positives are still an issue. Wise use of the genomic features around the fusion gene breakpoints will be helpful to identify reliable fusion genes efficiently. For this aim, we developed FusionAI,...

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Detalles Bibliográficos
Autores principales: Kim, Pora, Tan, Hua, Liu, Jiajia, Kumar, Himansu, Zhou, Xiaobo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892011/
https://www.ncbi.nlm.nih.gov/pubmed/35252882
http://dx.doi.org/10.1016/j.xpro.2022.101185
Descripción
Sumario:Even though there were many tool developments of fusion gene prediction from NGS data, too many false positives are still an issue. Wise use of the genomic features around the fusion gene breakpoints will be helpful to identify reliable fusion genes efficiently. For this aim, we developed FusionAI, a deep learning pipeline predicting human fusion gene breakpoints from DNA sequence. FusionAI is freely available via https://compbio.uth.edu/FusionGDB2/FusionAI. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021b).