TY - GEN
T1 - Gene network inference via sparse structural equation modeling with genetic perturbations
AU - Cai, Xiaodong
AU - Bazerque, Juan Andrés
AU - Giannakis, Georgios B.
PY - 2011/12/1
Y1 - 2011/12/1
N2 - Structural equation models (SEMs) have been recently proposed to infer gene regulatory network using gene expression data and genetic perturbations. However, lack of efficient inference method for SEMs prevents practical use of SEMs in the inference of relatively large gene networks. In this paper, relying on the sparsity of gene networks, we develop an efficient SEM-based method for inferring gene networks using both gene expression and expression quantitative trait locus (eQTL) data. Simulated tests demonstrate that the novel method significantly outperform state-of-the-art methods in the field.
AB - Structural equation models (SEMs) have been recently proposed to infer gene regulatory network using gene expression data and genetic perturbations. However, lack of efficient inference method for SEMs prevents practical use of SEMs in the inference of relatively large gene networks. In this paper, relying on the sparsity of gene networks, we develop an efficient SEM-based method for inferring gene networks using both gene expression and expression quantitative trait locus (eQTL) data. Simulated tests demonstrate that the novel method significantly outperform state-of-the-art methods in the field.
UR - http://www.scopus.com/inward/record.url?scp=84863699416&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863699416&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84863699416
SN - 9781467304900
T3 - Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
SP - 66
EP - 69
BT - Proceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
T2 - 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
Y2 - 4 December 2011 through 6 December 2011
ER -