title: Identifying gene pathways associated with cancer characteristics via sparse statistical methods.
abstract: We propose a statistical method for uncovering gene pathways that characterize cancer heterogeneity. To incorporate knowledge of the pathways into the model, we define a set of activities of pathways from microarray gene expression data based on the Sparse Probabilistic Principal Component Analysis (SPPCA). A pathway activity logistic regression model is then formulated for cancer phenotype. To select pathway activities related to binary cancer phenotypes, we use the elastic net for the parameter estimation and derive a model selection criterion for selecting tuning parameters included in the model estimation. Our proposed method can also reverse-engineer gene networks based on the identified multiple pathways that enables us to discover novel gene-gene associations relating with the cancer phenotypes. We illustrate the whole process of the proposed method through the analysis of breast cancer gene expression data.
authors.affiliation: Department of Mathematical Sciences, Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 599-8531, Japan. skawano@ms.osakafu-u.ac.jp
authors.forename: Shuichi
authors.initials: S
authors.lastname: Kawano
authors.forename: Teppei
authors.initials: T
authors.lastname: Shimamura
authors.forename: Atsushi
authors.initials: A
authors.lastname: Niida
authors.forename: Seiya
authors.initials: S
authors.lastname: Imoto
authors.forename: Rui
authors.initials: R
authors.lastname: Yamaguchi
authors.forename: Masao
authors.initials: M
authors.lastname: Nagasaki
authors.forename: Ryo
authors.initials: R
authors.lastname: Yoshida
authors.forename: Cristin
authors.initials: C
authors.lastname: Print
authors.forename: Satoru
authors.initials: S
authors.lastname: Miyano
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D016015:Logistic Models; D020411:Oligonucleotide Array Sequence Analysis; D025341:Principal Component Analysis