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Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data

Crossref DOI link: https://doi.org/10.1007/s00438-018-1454-1

Published Online: 2018-06-07

Published Print: 2018-10

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Paisitkriangkrai, Sakrapee

Quek, Kelly

Nievergall, Eva

Jabbour, Anissa

Zannettino, Andrew

Kok, Chung Hoow
License Information

Text and Data Mining valid from 2018-06-07
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Article History

Received: 27 October 2017

Accepted: 31 May 2018

First Online: 7 June 2018

Compliance with ethical standards

:

: Sakrapee Paisitkriangkrai declares that he has no conflict of interest. Kelly Quek declares that she has no conflict of interest. Eva Nievergall declares that she has no conflict of interest. Anissa Jabbour declares that she has no conflict of interest. Andrew Zannettino declares that he has no conflict of interest. Chung H Kok declares that he has no conflict of interest.

: This article does not contain any studies with human participants or animals performed by any of the authors.

: The RNA-seq leukemic cell lines dataset analysed during the current study is publicly available at Cancer Genomics Hub (ExternalRef removed<u>)</u> and NCI Genomic Data Commons (ExternalRef removed<u>)</u>. The raw sequencing data for 272 gliomas clinical samples dataset analysed during the current study is publicly available at NCBI Gene Expression Omnibus (GEO; ExternalRef removed) under accession number GSE48865. The raw FusionCatcher analysis results generated during this study are included in this published article as supplementary information files.