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FUNGI: FUsioN Gene Integration toolset
MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identific...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504624/ https://www.ncbi.nlm.nih.gov/pubmed/33772596 http://dx.doi.org/10.1093/bioinformatics/btab206 |
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author | Cervera, Alejandra Rausio, Heidi Kähkönen, Tiia Andersson, Noora Partel, Gabriele Rantanen, Ville Paciello, Giulia Ficarra, Elisa Hynninen, Johanna Hietanen, Sakari Carpén, Olli Lehtonen, Rainer Hautaniemi, Sampsa Huhtinen, Kaisa |
author_facet | Cervera, Alejandra Rausio, Heidi Kähkönen, Tiia Andersson, Noora Partel, Gabriele Rantanen, Ville Paciello, Giulia Ficarra, Elisa Hynninen, Johanna Hietanen, Sakari Carpén, Olli Lehtonen, Rainer Hautaniemi, Sampsa Huhtinen, Kaisa |
author_sort | Cervera, Alejandra |
collection | PubMed |
description | MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. RESULTS: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance. AVAILABILITYAND IMPLEMENTATION: FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8504624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85046242021-10-13 FUNGI: FUsioN Gene Integration toolset Cervera, Alejandra Rausio, Heidi Kähkönen, Tiia Andersson, Noora Partel, Gabriele Rantanen, Ville Paciello, Giulia Ficarra, Elisa Hynninen, Johanna Hietanen, Sakari Carpén, Olli Lehtonen, Rainer Hautaniemi, Sampsa Huhtinen, Kaisa Bioinformatics Applications Notes MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. RESULTS: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance. AVAILABILITYAND IMPLEMENTATION: FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-03-27 /pmc/articles/PMC8504624/ /pubmed/33772596 http://dx.doi.org/10.1093/bioinformatics/btab206 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Cervera, Alejandra Rausio, Heidi Kähkönen, Tiia Andersson, Noora Partel, Gabriele Rantanen, Ville Paciello, Giulia Ficarra, Elisa Hynninen, Johanna Hietanen, Sakari Carpén, Olli Lehtonen, Rainer Hautaniemi, Sampsa Huhtinen, Kaisa FUNGI: FUsioN Gene Integration toolset |
title | FUNGI: FUsioN Gene Integration toolset |
title_full | FUNGI: FUsioN Gene Integration toolset |
title_fullStr | FUNGI: FUsioN Gene Integration toolset |
title_full_unstemmed | FUNGI: FUsioN Gene Integration toolset |
title_short | FUNGI: FUsioN Gene Integration toolset |
title_sort | fungi: fusion gene integration toolset |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504624/ https://www.ncbi.nlm.nih.gov/pubmed/33772596 http://dx.doi.org/10.1093/bioinformatics/btab206 |
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