Back to Search
Start Over
Characteristic gene selection via weighting principal components by singular values.
- Source :
-
PloS one [PLoS One] 2012; Vol. 7 (7), pp. e38873. Date of Electronic Publication: 2012 Jul 10. - Publication Year :
- 2012
-
Abstract
- Conventional gene selection methods based on principal component analysis (PCA) use only the first principal component (PC) of PCA or sparse PCA to select characteristic genes. These methods indeed assume that the first PC plays a dominant role in gene selection. However, in a number of cases this assumption is not satisfied, so the conventional PCA-based methods usually provide poor selection results. In order to improve the performance of the PCA-based gene selection method, we put forward the gene selection method via weighting PCs by singular values (WPCS). Because different PCs have different importance, the singular values are exploited as the weights to represent the influence on gene selection of different PCs. The ROC curves and AUC statistics on artificial data show that our method outperforms the state-of-the-art methods. Moreover, experimental results on real gene expression data sets show that our method can extract more characteristic genes in response to abiotic stresses than conventional gene selection methods.
- Subjects :
- Algorithms
Arabidopsis radiation effects
Area Under Curve
Cold Temperature
Droughts
Gene Expression Profiling
Plant Roots radiation effects
Plant Shoots radiation effects
ROC Curve
Salinity
Stress, Physiological
Ultraviolet Rays
Arabidopsis genetics
Arabidopsis Proteins genetics
Gene Expression Regulation, Plant radiation effects
Plant Roots genetics
Plant Shoots genetics
Principal Component Analysis methods
Subjects
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 7
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 22808018
- Full Text :
- https://doi.org/10.1371/journal.pone.0038873