compound.Cox-package {compound.Cox}R Documentation

Univariate Feature Selection and Compound Covariate for Predicting Survival

Description

Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med), statistical methods in Emura et al (2012 PLoS ONE), Emura & Chen (2016 Stat Methods Med Res), and Emura et al. (2019 Comput Methods Programs Biomed). Algorithms for generating correlated gene expressions are also available.

Details

Package: compound.Cox
Type: Package
Version: 3.20
Date: 2020-7-4
License: GPL-2

Author(s)

Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen; Maintainer: Takeshi Emura <takeshiemura@gmail.com>

References

Chen HY, Yu SL, Chen CH, et al (2007). A Five-gene Signature and Clinical Outcome in Non-small-cell Lung Cancer, N Engl J Med 356: 11-20.

Emura T, Chen YH, Chen HY (2012). Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models. PLoS ONE 7(10): e47627. doi:10.1371/journal.pone.0047627

Emura T, Chen YH (2016). Gene Selection for Survival Data Under Dependent Censoring: a Copula-based Approach, Stat Methods Med Res 25(No.6): 2840-57

Emura T, Matsui S, Chen HY (2019). compound.Cox: Univariate Feature Selection and Compound Covariate for Predicting Survival, Computer Methods and Programs in Biomedicine 168: 21-37

Matsui S (2006). Predicting Survival Outcomes Using Subsets of Significant Genes in Prognostic Marker Studies with Microarrays. BMC Bioinformatics: 7:156.


[Package compound.Cox version 3.20 Index]