Deena M A Gendoo1, Natchar Ratanasirigulchai2, Markus S Schröder3, Laia Paré4, Joel S Parker5, Aleix Prat6, Benjamin Haibe-Kains1. 1. Bioinformatics and Computational Laboratory, Princess Margaret Cancer Centre, University Health Network and Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada. 2. Bioinformatics and Computational Laboratory, Princess Margaret Cancer Centre, University Health Network and. 3. UCD School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, UK. 4. Translational Genomics and Targeted Therapeutics in Solid Tumors, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain. 5. Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA. 6. Translational Genomics and Targeted Therapeutics in Solid Tumors, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain, Translational Genomics Group, Vall d'Hebron Institute of Oncology (VHIO), 08035 Barcelona, Spain and Department of Medical Oncology, Hospital Clínic of Barcelona, 08036 Barcelona, Spain.
Abstract
UNLABELLED: Breast cancer is one of the most frequent cancers among women. Extensive studies into the molecular heterogeneity of breast cancer have produced a plethora of molecular subtype classification and prognosis prediction algorithms, as well as numerous gene expression signatures. However, reimplementation of these algorithms is a tedious but important task to enable comparison of existing signatures and classification models between each other and with new models. Here, we present the genefu R/Bioconductor package, a multi-tiered compendium of bioinformatics algorithms and gene signatures for molecular subtyping and prognostication in breast cancer. AVAILABILITY AND IMPLEMENTATION: The genefu package is available from Bioconductor. http://www.bioconductor.org/packages/devel/bioc/html/genefu.html Source code is also available on Github https://github.com/bhklab/genefu CONTACT: bhaibeka@uhnresearch.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
UNLABELLED: Breast cancer is one of the most frequent cancers among women. Extensive studies into the molecular heterogeneity of breast cancer have produced a plethora of molecular subtype classification and prognosis prediction algorithms, as well as numerous gene expression signatures. However, reimplementation of these algorithms is a tedious but important task to enable comparison of existing signatures and classification models between each other and with new models. Here, we present the genefu R/Bioconductor package, a multi-tiered compendium of bioinformatics algorithms and gene signatures for molecular subtyping and prognostication in breast cancer. AVAILABILITY AND IMPLEMENTATION: The genefu package is available from Bioconductor. http://www.bioconductor.org/packages/devel/bioc/html/genefu.html Source code is also available on Github https://github.com/bhklab/genefu CONTACT: bhaibeka@uhnresearch.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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