This document explains the functionalities available in the a4Core package.
This package contains utility functions for the Automated Affymetrix Array Analysis suite of packages.
An expressionSet example data for testing and demonstration of the set of packages is simulated with the simulateData function:
eSet <- simulateData(
nCols = 40, nRows = 1000,
nEffectRows = 5, nNoEffectCols = 5,
betweenClassDifference = 1, withinClassSd = 0.5
)
print(eSet)## ExpressionSet (storageMode: lockedEnvironment)
## assayData: 1000 features, 40 samples
## element names: exprs
## protocolData: none
## phenoData
## sampleNames: Sample1 Sample2 ... Sample40 (40 total)
## varLabels: type
## varMetadata: type labelDescription
## featureData: none
## experimentData: use 'experimentData(object)'
## Annotation:The package contains utility functions to create the top tables of the most important features for multiple classification models as produced by the lassoClass function of the a4Classif package, as ‘glmnet’, ‘lognet’ and ‘elnet’.
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows Server 2012 R2 x64 (build 9600)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=C
## [2] LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] a4Core_1.38.0
##
## loaded via a namespace (and not attached):
## [1] codetools_0.2-16 lattice_0.20-41 foreach_1.5.1
## [4] glmnet_4.0-2 digest_0.6.27 grid_4.0.3
## [7] magrittr_1.5 evaluate_0.14 rlang_0.4.8
## [10] stringi_1.5.3 Matrix_1.2-18 rmarkdown_2.5
## [13] splines_4.0.3 iterators_1.0.13 tools_4.0.3
## [16] stringr_1.4.0 Biobase_2.50.0 parallel_4.0.3
## [19] survival_3.2-7 xfun_0.18 yaml_2.2.1
## [22] compiler_4.0.3 BiocGenerics_0.36.0 shape_1.4.5
## [25] htmltools_0.5.0 knitr_1.30