Modular network construction using eQTL data: an analysis of computational costs and benefits

被引:9
作者
Ho, Yen-Yi [1 ]
Cope, Leslie M. [2 ]
Parmigiani, Giovanni [3 ,4 ]
机构
[1] Univ Minnesota, Sch Publ Hlth, Div Biostat, Minneapolis, MN 55403 USA
[2] Johns Hopkins Sch Med, Sidney Kimmel Canc Ctr, Baltimore, MD USA
[3] Dana Farber Canc Inst, Boston, MA 02115 USA
[4] Harvard Univ, Sch Publ Hlth, Boston, MA 02115 USA
来源
FRONTIERS IN GENETICS | 2014年 / 5卷
关键词
HUMAN GENE-EXPRESSION; MOLECULAR NETWORKS; GENOMICS APPROACH; IDENTIFICATION; DISCOVERY; PATHWAYS; DISEASE; OBESITY; CELLS;
D O I
10.3389/fgene.2014.00040
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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.
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页数:16
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