ArticleFrontiers in genetics2014
Modular network construction using eQTL data: an analysis of computational costs and benefits.
Article in Frontiers in genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Modeling dynamic correlation in zero-inflated bivariate count data with applications to single-cell RNA sequencing data.Biometrics · 2022Article
- Interpreting Functional Impact of Genetic Variations by Network QTL for Genotype-Phenotype Association Study.Frontiers in cell and developmental biology · 2021Article
- An omics perspective on drug target discovery platforms.Briefings in bioinformatics · 2020Article
- A deep auto-encoder model for gene expression prediction.BMC genomics · 2017Article
- The Importance of Endophenotypes to Evaluate the Relationship between Genotype and External Phenotype.International journal of molecular sciences · 2017Review
- Quantitative assessment and validation of network inference methods in bioinformatics.Frontiers in genetics · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundIn 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.
resultsWe 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.
conclusionIn 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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Registered trials
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