ArticleBioinformatics (Oxford, England)2009
Graph theoretical approach to study eQTL: a case study of Plasmodium falciparum.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Interpreting Functional Impact of Genetic Variations by Network QTL for Genotype-Phenotype Association Study.Frontiers in cell and developmental biology · 2021Article
- Fast and robust group-wise eQTL mapping using sparse graphical models.BMC bioinformatics · 2015Article
- Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.Molecular bioSystems · 2012Article
- Metabolomics and malaria biology.Molecular and biochemical parasitology · 2011Review
- Co-regulatory expression quantitative trait loci mapping: method and application to endometrial cancer.BMC medical genomics · 2011Article
- A statistical approach to finding overlooked genetic associations.BMC bioinformatics · 2010Article
- Data-driven assessment of eQTL mapping methods.BMC genomics · 2010Article
- Recent Progress in Functional Genomic Research in Plasmodium falciparum.Current genomics · 2010Article
- Toward the dynamic interactome: it's about time.Briefings in bioinformatics · 2010Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationAnalysis of expression quantitative trait loci (eQTL) significantly contributes to the determination of gene regulation programs. However, the discovery and analysis of associations of gene expression levels and their underlying sequence polymorphisms continue to pose many challenges. Methods are limited in their ability to illuminate the full structure of the eQTL data. Most rely on an exhaustive, genome scale search that considers all possible locus-gene pairs and tests the linkage between each locus and gene.
resultTo analyze eQTLs in a more comprehensive and efficient way, we developed the Graph based eQTL Decomposition method (GeD) that allows us to model genotype and expression data using an eQTL association graph. Through graph-based heuristics, GeD identifies dense subgraphs in the eQTL association graph. By identifying eQTL association cliques that expose the hidden structure of genotype and expression data, GeD effectively filters out most locus-gene pairs that are unlikely to have significant linkage. We apply GeD on eQTL data from Plasmodium falciparum, the human malaria parasite, and show that GeD reveals the structure of the relationship between all loci and all genes on a whole genome level. Furthermore, GeD allows us to uncover additional eQTLs with lower FDR, providing an important complement to traditional eQTL analysis methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.