TY - JOUR
T1 - Statistical methods for identifying differentially expressed gene combinations.
AU - Ho, Yen Yi
AU - Cope, Leslie
AU - Dettling, Marcel
AU - Parmigiani, Giovanni
PY - 2007
Y1 - 2007
N2 - Identification of coordinate gene expression changes across phenotypes or biological conditions is the basis of the ability to decode the role of gene expression regulatory networks. Statistically, the identification of these changes can be viewed as a search for groups (most typically pairs) of genes whose expression provides better phenotype discrimination when considered jointly than when considered individually. Such groups are defined as being jointly differentially expressed. In this chapter several approaches for identifying jointly differentially expressed groups of genes are reviewed of compared on a set of simulations.
AB - Identification of coordinate gene expression changes across phenotypes or biological conditions is the basis of the ability to decode the role of gene expression regulatory networks. Statistically, the identification of these changes can be viewed as a search for groups (most typically pairs) of genes whose expression provides better phenotype discrimination when considered jointly than when considered individually. Such groups are defined as being jointly differentially expressed. In this chapter several approaches for identifying jointly differentially expressed groups of genes are reviewed of compared on a set of simulations.
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U2 - 10.1007/978-1-59745-547-3_10
DO - 10.1007/978-1-59745-547-3_10
M3 - Article
C2 - 18314583
AN - SCOPUS:41449090061
SN - 1064-3745
VL - 408
SP - 171
EP - 191
JO - Methods in molecular biology (Clifton, N.J.)
JF - Methods in molecular biology (Clifton, N.J.)
ER -