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This function computes signature scores and risk classifications from gene expression values following the algorithm used for the endoPredict signature as published by Filipits et al 2011.
● Data Source:
BioConductor
● Keywords: prognosis
● Alias: endoPredict
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This dataset contains (part of) the gene expression, annotations and clinical data from the expO dataset collected by the International Genomics Consortium (http://www.intgen.org/expo/).
● Data Source:
BioConductor
● Keywords: data
● Alias: annot.expos, data.expos, demo.expos, expos
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This function allows for computing the weighted mean and weighted variance of a vector of continuous values.
● Data Source:
BioConductor
● Keywords: htest
● Alias: fuzzy.ttest
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This function computes signature scores and risk classifications from gene expression values following the algorithm used for the 70 genes prognosis profile (GENE70) as published by van't Veer et al. 2002.
● Data Source:
BioConductor
● Keywords: prognosis
● Alias: gene70
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This function computes signature scores and risk classifications from gene expression values following the algorithm used for the Relapse Score (GENE76) as published by Wang et al. 2005.
● Data Source:
BioConductor
● Keywords: prognosis
● Alias: gene76
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This package contains functions implementing various tasks usually required by gene expression analysis, especially in breast cancer studies: gene mapping between different microarray platforms, identification of molecular subtypes, implementation of published gene signatures, gene selection, survival analysis, ...
● Data Source:
BioConductor
● Keywords: breast cancer, clustering, models, prognosis
● Alias: genefu, genefu-package
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This function allows for fast mapping between two datasets or a dataset and a gene list. The mapping process is performed using Entrez Gene id as reference. In case of ambiguities (several probes representing the same gene), the most variant probe is selected.
● Data Source:
BioConductor
● Keywords: mapping
● Alias: geneid.map
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This function computes the Gene Expression progNostic Index Using Subtypes (GENIUS) as published by Haibe-Kains et al. 2010. Subtype-specific risk scores are computed for each subtype signature separately and an overall risk score is computed by combining these scores with the posterior probability to belong to each of the breast cancer molecular subtypes.
● Data Source:
BioConductor
● Keywords: prognosis
● Alias: genius
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This function computes signature scores and risk classifications from gene expression values following the algorithm used for the Gene expression Grade Index (GGI).
● Data Source:
BioConductor
● Keywords: prognosis
● Alias: ggi
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This function computes the prognostic score based on four measured IHC markers (ER, PGR, HER2, Ki-67), following the algorithm as published by Cuzick et al. 2011. The user has the option to either obtain just the shrinkage-adjusted IHC4 score (IHC4) or the overall score htat also combines the clinical score (IHC4+C)
● Data Source:
BioConductor
● Keywords: prognosis
● Alias: ihc4
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