ClassifieR 2.0: expanding interactive gene expression-based stratification to prostate and high-grade serous ovarian cancer

ClassifieR 2.0 combines molecular subtyping of prostate cancer and HGSOC with commonly used sample annotation tools in a single, user-friendly platform, allowing scientists without bioinformatics training to explore prostate and HGSOC transcriptional data without the need for extensive bioinformatics knowledge or manual data handling to operate various packages. Our sigInfer method within ClassifieRp enables the inference of commercially available gene signatures for prostate cancer, while ClassifieRov incorporates consensus molecular subtyping for HGSOC. Overall, ClassifieR 2.0 aims to make molecular subtyping more accessible to the wider research community. This is crucial for increased understanding of the molecular heterogeneity of these cancers and developing personalised treatment strategies.

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Publication Details

Journal
BMC Bioinformatics
Published
2024-11-21
DOI
https://doi.org/10.1186/s12859-024-05981-6
Citations
1
Primary Topic
Cancer, Lipids, and Metabolism
Type
article
Field-Weighted Citation Impact
0.29

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ClassifieR 2.0: expanding interactive gene expression-based stratification to prostate and high-grade serous ovarian cancer

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BMC Bioinformatics
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article

ClassifieR 2.0: expanding interactive gene expression-based stratification to prostate and high-grade serous ovarian cancer

Aideen McCabe, Gerard P. Quinn, Ross G. Murphy, Kellie Dean, Simon S. McDade, Suneil Jain, Micheál Ó. Dálaigh
article en
1 citations

Abstract

ClassifieR 2.0 combines molecular subtyping of prostate cancer and HGSOC with commonly used sample annotation tools in a single, user-friendly platform, allowing scientists without bioinformatics training to explore prostate and HGSOC transcriptional data without the need for extensive bioinformatics knowledge or manual data handling to operate various packages. Our sigInfer method within ClassifieRp enables the inference of commercially available gene signatures for prostate cancer, while ClassifieRov incorporates consensus molecular subtyping for HGSOC. Overall, ClassifieR 2.0 aims to make molecular subtyping more accessible to the wider research community. This is crucial for increased understanding of the molecular heterogeneity of these cancers and developing personalised treatment strategies.

BMC BioinformaticsVol. 25(1)
Queen's University Belfast (GB), Belfast Health and Social Care Trust (GB), University of Ulster (GB), Science Foundation Ireland (IE), Ollscoil na Gaillimhe – University of Galway (IE), University College Cork (IE), Department for Infrastructure (GB)
Movember Foundation, Cancer Research UK, Science Foundation Ireland, Medical Research Council
Good health and well-being
Openalex Percentile: Top 37%
Cancer, Lipids, and Metabolism
0.29
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