LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data

Stat Appl Genet Mol Biol. 2019 Feb 13;18(2):/j/sagmb.2019.18.issue-2/sagmb-2017-0060/sagmb-2017-0060.xml. doi: 10.1515/sagmb-2017-0060.

Abstract

Longitudinal genomics data and survival outcome are common in biomedical studies, where the genomics data are often of high dimension. It is of great interest to select informative longitudinal biomarkers (e.g. genes) related to the survival outcome. In this paper, we develop a computationally efficient tool, LCox, for selecting informative biomarkers related to the survival outcome using the longitudinal genomics data. LCox is powerful to detect different forms of dependence between the longitudinal biomarkers and the survival outcome. We show that LCox has improved performance compared to existing methods through extensive simulation studies. In addition, by applying LCox to a dataset of patients with idiopathic pulmonary fibrosis, we are able to identify biologically meaningful genes while all other methods fail to make any discovery. An R package to perform LCox is freely available at https://CRAN.R-project.org/package=LCox.

Keywords: biomarker identification; longitudinal gene expression data; survival outcomes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Computational Biology / statistics & numerical data*
  • Gene Expression Profiling / statistics & numerical data
  • Genomics / statistics & numerical data*
  • Humans
  • Software*
  • Survival Analysis*