title: A Phenotype-Driven Dimension Reduction (PhDDR) approach to integrated genomic association analyses.
abstract: An immediate challenge in integrated genomic analysis involving several types of genomic factors all measured genome-wide is the ultra-high dimensionality. Screening all possible relationships among the genomic factors is an NP-hard problem; therefore in practice proper dimension reduction is necessary. In this paper we develop the Phenotype-Driven Dimension Reduction (PhDDR) approach to the analysis of gene co-expressions, and discuss its extensions to integration of other genetic factors. This approach is then illustrated by an application to gene co-expression analysis of treatment response of childhood leukemia.
authors.affiliation: Department of Biostatistics, St Jude Children’s Research Hospital, Memphis, TN 38105, USA.
authors.forename: Cuilan
authors.initials: C
authors.lastname: Gao
authors.forename: Cheng
authors.initials: C
authors.lastname: Cheng
mesh_terms: D000465:Algorithms; D002648:Child; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods; D015973:Gene Expression Regulation, Leukemic; D023281:Genomics; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D010641:Phenotype; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000378:metabolism*; D011336:Probability; D011379:Prognosis; D012107:Research Design; D012984:Software