cvmv

A matrix of survival information for the training dataset.
It has three columns representing the estimated HR, the 95% lower
confidence interval and the 95% upper confidence interval.

HRTrain

A matrix of survival information for the test dataset.
It has three columns representing the estimated HR, the 95%
lower confidence interval and the 95% upper confidence interval.

HRTest

The number of cross validation used

The Metabolite data matrix that was used for the analysis
either same as Mdata or a reduced version.

Mdata

The names of prognostic factors used

Progfact

An approach to identifies metabolic biomarker signature for metabolic data by discovering predictive metabolite for predicting survival and classifying patients into risk groups.
Classifiers are constructed as a linear combination of predictive/important metabolites, prognostic factors and treatment effects if necessary.
Several methods were implemented to reduce the metabolomics matrix such as the principle component analysis of Wold Svante et al. (1987) <doi:10.1016/0169-7439(87)80084-9> ,
the LASSO method by Robert Tibshirani (1998) <doi:10.1002/(SICI)1097-0258(19970228)16:4%3C385::AID-SIM380%3E3.0.CO;2-3>, the
elastic net approach by Hui Zou and Trevor Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.
Sensitivity analysis on the quantile used for the classification can also be accessed to check the deviation of the classification group based on the quantile specified.
Large scale cross validation can be performed in order to investigate the mostly selected predictive metabolites and for internal validation. During the evaluation process, validation is accessed using the hazard ratios (HR) distribution of the test set and inference is mainly based on resampling and permutations technique.

cvmv: Constructor for the cvmv class

Description

Usage

Arguments

Value