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Construction of subtype‑specific prognostic gene signatures for early‑stage non‑small cell lung cancer using meta feature selection methods
- Source :
- Oncology Letters
- Publication Year :
- 2019
- Publisher :
- Spandidos Publications, 2019.
-
Abstract
- Feature selection in the framework of meta-analyses (meta feature selection), combines meta-analysis with a feature selection process and thus allows meta-analysis feature selection across multiple datasets. In the present study, a meta feature selection procedure that fitted a multiple Cox regression model to estimate the effect size of a gene in individual studies and to identify the overall effect of the gene using a meta-analysis model was proposed. The method was used to identify prognostic gene signatures for lung adenocarcinoma and lung squamous cell carcinoma. Furthermore, redundant gene elimination (RGE) is of crucial importance during feature selection, and is also essential for a meta feature selection process. The current study demonstrated that the proposed meta feature selection procedure with RGE outperforms that without RGE in terms of predictive ability, model parsimony and biological interpretation.
- Subjects :
- 0301 basic medicine
Cancer Research
Computer science
Feature selection
Computational biology
03 medical and health sciences
feature selection
0302 clinical medicine
redundant gene elimination
medicine
Stage (cooking)
Lung cancer
Gene
non-small cell lung cancer
Proportional hazards model
Lung squamous cell carcinoma
Articles
medicine.disease
meta-analysis
030104 developmental biology
Oncology
Cox model
030220 oncology & carcinogenesis
Meta-analysis
prognosis
Non small cell
Subjects
Details
- ISSN :
- 17921082 and 17921074
- Database :
- OpenAIRE
- Journal :
- Oncology Letters
- Accession number :
- edsair.doi.dedup.....1eb0ddcc750097828680dcec612a805b