Artifacts using GolubEsets (6)
1. Biobase360 usages
org.renjin.bioconductor » BiobaseArtistic
Functions that are needed by many other packages or which replace R functions.
Last Release on Feb 14, 2021
The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.
Last Release on Apr 28, 2022
In a typical microarray setting with gene expression data observed under two conditions, the local false discovery rate describes the probability that a gene is not differentially expressed between the two conditions given its corrresponding observed score or p-value level. The resulting curve of p-values versus local false discovery rate offers an insight into the twilight zone between clear differential and clear non-differential gene expression. Package 'twilight' contains two main functions: Function ...
Last Release on Apr 28, 2022
Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a new method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new ...
Last Release on Apr 29, 2022
This package includes a function for combining preprocessing and classification methods to calculate misclassification errors
Last Release on Apr 29, 2022
6. Pvca
org.renjin.bioconductor » pvcaLGPL
This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12.
Last Release on Apr 28, 2022
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