Package: MetabolicSurv
Type: Package
Title: A Biomarker Validation Approach for Classification and
        Predicting Survival Using Metabolomics Signature
Version: 1.1.0
Authors@R: c(
       person("Olajumoke Evangelina","Owokotomo",email="olajumoke.owokotomo@uhasselt.be",role=c("aut","cre")),
       person("Ziv","Shkedy",email="ziv.shkedy@uhasselt.be",role="aut"))
Maintainer: Olajumoke Evangelina Owokotomo
 <olajumoke.owokotomo@uhasselt.be>
Description: 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.
URL: https://github.com/OlajumokeEvangelina/MetabolicSurv
BugReports: https://github.com/OlajumokeEvangelina/MetabolicSurv/issues/new
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0)
Imports: superpc, glmnet, matrixStats, survminer, survival, rms, tidyr,
        pls, Rdpack, methods, stats, gplots, ggplot2
RdMacros: Rdpack
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Config/pak/sysreqs: cmake make libicu-dev libjpeg-dev libpng-dev
        libuv1-dev libxml2-dev libssl-dev
Repository: https://olajumokeevangelina.r-universe.dev
Date/Publication: 2019-08-06 11:06:08 UTC
RemoteUrl: https://github.com/olajumokeevangelina/metabolicsurv
RemoteRef: HEAD
RemoteSha: 3cba18aed0faae708ef10f9aaa280c6127391a59
NeedsCompilation: no
Packaged: 2026-10-04 08:50:53 UTC; root
Author: Olajumoke Evangelina Owokotomo [aut, cre],
  Ziv Shkedy [aut]