DaMiR.Allplot |
Quality assessment and visualization of expression data |
DaMiR.Clustplot |
Expression data clustering and heatmap |
DaMiR.corrplot |
Correlation Plot |
DaMiR.EnsembleLearning |
Build Classifier using 'Staking' Ensemble Learning strategy. |
DaMiR.EnsembleLearning2cl |
Build a Binary Classifier using 'Staking' Learning strategy. |
DaMiR.EnsembleLearningNcl |
Build a Multi-Class Classifier using 'Staking' Learning strategy. |
DaMiR.FBest |
Select best predictors to build Classification Model |
DaMiR.FReduct |
Remove highly correlated features, based on feature-per-feature correlation. |
DaMiR.FSelect |
Feature selection for classification |
DaMiR.FSort |
Order features by importance, using RReliefF filter |
DaMiR.goldenDice |
Generate a Number to Set Seed |
DaMiR.makeSE |
Import RNA-Seq count data and variables |
DaMiR.MDSplot |
Plot multidimentional scaling (MDS) |
DaMiR.normalization |
Filter non Expressed and 'Hypervariant' features and Data Normalization |
DaMiR.sampleFilt |
Filter Samples by Mean Correlation Distance Metric |
DaMiR.SV |
Identification of Surrogate Variables |
DaMiR.SVadjust |
Remove variable effects from expression data |
DaMiR.transpose |
Matrix transposition and replacement of '.' and '-' special characters |
data_min |
Example gene-expression dataset for DaMiRseq package |
data_norm |
A dataset with a normalized matrix to test several DaMiRseq functions: sample data are a subset of Genotype-Tissue Expression (GTEx) RNA-Seq database (dbGap Study Accession: phs000424.v6.p1) |
data_reduced |
Example gene-expression dataset for DaMiRseq package |
data_relief |
Example ranking dataset for DaMiRseq package |
df |
Example gene-expression dataset for DaMiRseq package |
SE |
Example gene-expression dataset for DaMiRseq package |
selected_features |
Example gene-expression dataset for DaMiRseq package |
SEtest_norm |
A sample dataset with a normalized count matrix for "testthat" functions. |
sv |
Example Surrogate Variables dataset for DaMiRseq package |