imirage.cv.loop: iMIRAGE cross-validation loop function for full miRNA matrix

In aritronath/iMIRAGE: iMIRAGE: imputed miRNA activity from gene expression (Title Case)

Description

Convinient wrapper for imirage.cv that performs cross-validation analysis for assessing imputation accuracies for all miRNAs using the training datasets

Usage

imirage.cv.loop(train_pcg, train_mir, method = "KNN", ...)

Arguments

train_pcg	training protein coding dataset. a numeric matrix with with row names indicating samples, and column names indicating protein coding gene IDs.
train_mir	training miRNA expression dataset. a numeric matrix with row names indicating samples, and column names indicating miRNA IDs.
method	method for imputation, either "RF" for random forests, "KNN" for K-nearest neighbor or "SVM" for support vector machines.
...	optional parameters that can be passed on to the machine-learning method: RF (randomForest), KNN (knn.reg) or SVM(svm)

Value

a matrix containing Spearman's correlation coefficient, P-value and RMSE from the cross-validation analysis of the complete miRNA training dataset

Examples

imirage.cv.loop(train_pcg = GA.pcg, train_mir = GA.mir, method = "KNN")
imirage.cv.loop(train_pcg = GA.pcg, train_mir = GA.mir, method = "SVM")

aritronath/iMIRAGE documentation built on Dec. 29, 2019, 1:28 a.m.