Scientific article
Open access

A predictive based regression algorithm for gene network selection

Published inFrontiers in genetics, vol. 7
Publication date2016

Gene selection has become a common task in most gene expression studies. The objective of such research is often to identify the smallest possible set of genes that can still achieve good predictive performance. To do so, many of the recently proposed classification methods require some form of dimension-reduction of the problem which finally provide a single model as an output and, in most cases, rely on the likelihood function in order to achieve variable selection. We propose a new prediction-based objective function that can be tailored to the requirements of practitioners and can be used to assess and interpret a given problem. Based on cross-validation techniques and the idea of importance sampling, our proposal scans low-dimensional models under the assumption of sparsity and, for each of them, estimates their objective function to assess their predictive power in order to select. Two applications on cancer data sets and a simulation study show that the proposal compares favorably with competing alternatives such as, for example, Elastic Net and Support Vector Machine. Indeed, the proposed method not only selects smaller models for better, or at least comparable, classification errors but also provides a set of selected models instead of a single one, allowing to construct a network of possible models for a target prediction accuracy level.

  • Biomarker selection
  • Genomic network
  • Disease classification
  • Breast cancer
  • Acute leukemia
  • Model averaging
Citation (ISO format)
GUERRIER, Stéphane et al. A predictive based regression algorithm for gene network selection. In: Frontiers in genetics, 2016, vol. 7. doi: 10.3389/fgene.2016.00097
Main files (1)
Article (Published version)
ISSN of the journal1664-8021

Technical informations

Creation08/01/2017 4:20:00 PM
First validation08/01/2017 4:20:00 PM
Update time03/15/2023 1:54:47 AM
Status update03/15/2023 1:54:47 AM
Last indexation01/17/2024 12:26:57 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack