%A Ho,Yen-Yi %A Cope,Leslie %A Parmigiani,Giovanni %D 2014 %J Frontiers in Genetics %C %F %G English %K Search algorithm,Network variable selection,chemotherapy resistance,bayesian networks,eQTL %Q %R 10.3389/fgene.2014.00040 %W %L %M %P %7 %8 2014-February-26 %9 Methods %+ Dr Yen-Yi Ho,University of Minnesota,Division of Biostatistics, School of Public Health,420 Delaware St. SE,Mayo Memorial Building, MMC 303,Minneapolis,55455,MN,United States,yho@umn.edu %# %! Network partition and re-assembly search algorithm %* %< %T Modular network construction using eQTL data: an analysis of computational costs and benefits %U https://www.frontiersin.org/articles/10.3389/fgene.2014.00040 %V 5 %0 JOURNAL ARTICLE %@ 1664-8021 %X Background: In this paper, we consider analytic methods for the integrated analysis of genomic DNA variation and mRNA expression (also named as eQTL data), to discover genetic networks that are associated with a complex trait of interest. Our focus is the systematic evaluation of the trade-off between network size and network search efficiency in the construction of these networks.Results: We developed a modular approach to network construction, building from smaller networks to larger ones, thereby reducing the search space while including more variables in the analysis. The goal is achieving a lower computational cost while maintaining high confidence in the resulting networks. As demonstrated in our simulation results, networks built in this way have low node/edge false discovery rate (FDR) and high edge sensitivity comparing to greedy search. We further demonstrate our method in a data set of cellular responses to two chemotherapeutic agents: docetaxel and 5-fluorouracil (5-FU), and identify biologically plausible networks that might describe resistances to these drugs.Conclusion: In this study, we suggest that guided comprehensive searches for parsimonious networks should be considered as an alternative to greedy network searches.