In this paper, based on robust PCA, a novel method of characteristic genes identification is proposed. In our method, the differentially expressed genes and non-differentially expressed genes are treated as perturbation signals S 0 and low-rank matrix A 0, respectively, which can be recovered from the gene expression data using robust PCA. The scheme to identify the characteristic genes is as following. Firstly, the matrix S 0 of perturbation signals is discovered from gene expression data matrix D by using robust PCA. Secondly, the characteristic genes are selected according to matrix S 0. Finally, the characteristic genes are checked by the tool of Gene Ontology. The experimental results show that our method is efficient and effective. © 2012 Springer-Verlag.
CITATION STYLE
Zheng, C. H., Liu, J. X., Mi, J. X., & Xu, Y. (2012). Identifying characteristic genes based on robust principal component analysis. In Communications in Computer and Information Science (Vol. 304 CCIS, pp. 174–179). https://doi.org/10.1007/978-3-642-31837-5_25
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