Your browser doesn't support javascript.
loading
Fusion-Bloom: fusion detection in assembled transcriptomes.
Chiu, Readman; Nip, Ka Ming; Birol, Inanc.
Afiliação
  • Chiu R; Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada.
  • Nip KM; Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada.
  • Birol I; Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC V6H 3N1, Canada.
Bioinformatics ; 36(7): 2256-2257, 2020 04 01.
Article em En | MEDLINE | ID: mdl-31790154
ABSTRACT

SUMMARY:

Presence or absence of gene fusions is one of the most important diagnostic markers in many cancer types. Consequently, fusion detection methods using various genomics data types, such as RNA sequencing (RNA-seq) are valuable tools for research and clinical applications. While information-rich RNA-seq data have proven to be instrumental in discovery of a number of hallmark fusion events, bioinformatics tools to detect fusions still have room for improvement. Here, we present Fusion-Bloom, a fusion detection method that leverages recent developments in de novo transcriptome assembly and assembly-based structural variant calling technologies (RNA-Bloom and PAVFinder, respectively). We benchmarked Fusion-Bloom against the performance of five other state-of-the-art fusion detection tools using multiple datasets. Overall, we observed Fusion-Bloom to display a good balance between detection sensitivity and specificity. We expect the tool to find applications in translational research and clinical genomics pipelines. AVAILABILITY AND IMPLEMENTATION Fusion-Bloom is implemented as a UNIX Make utility, available at https//github.com/bcgsc/pavfinder and released under a Creative Commons License (Attribution 4.0 International), as described at http//creativecommons.org/licenses/by/4.0/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Transcriptoma Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Transcriptoma Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article