Ho, Yen-YiCope, Leslie M.Parmigiani, Giovanni2014-04-112014Ho, Yen-Yi, Leslie M. Cope, and Giovanni Parmigiani. 2014. “Modular network construction using eQTL data: an analysis of computational costs and benefits.” Frontiers in Genetics 5 (1): 40. doi:10.3389/fgene.2014.00040. http://dx.doi.org/10.3389/fgene.2014.00040.1664-8021http://nrs.harvard.edu/urn-3:HUL.InstRepos:12064408Background: 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.en-USMethods ArticleBayesian networkssearch algorithmnetwork variable selectioneQTLchemotherapy resistanceJournal Article2014-04-1110.3389/fgene.2014.00040