Data-driven assessment of eQTL mapping methods.
dc.contributor.author | Michaelson, Jacob J | |
dc.contributor.author | Alberts, Rudi | |
dc.contributor.author | Schughart, Klaus | |
dc.contributor.author | Beyer, Andreas | |
dc.date.accessioned | 2011-03-02T11:51:15Z | en |
dc.date.available | 2011-03-02T11:51:15Z | en |
dc.date.issued | 2010 | en |
dc.identifier.citation | Data-driven assessment of eQTL mapping methods. 2010, 11:502 BMC Genomics | en |
dc.identifier.issn | 1471-2164 | en |
dc.identifier.pmid | 20849587 | en |
dc.identifier.doi | 10.1186/1471-2164-11-502 | en |
dc.identifier.uri | http://hdl.handle.net/10033/123291 | en |
dc.description.abstract | The analysis of expression quantitative trait loci (eQTL) is a potentially powerful way to detect transcriptional regulatory relationships at the genomic scale. However, eQTL data sets often go underexploited because legacy QTL methods are used to map the relationship between the expression trait and genotype. Often these methods are inappropriate for complex traits such as gene expression, particularly in the case of epistasis. | |
dc.language.iso | en | en |
dc.subject.mesh | Animals | en |
dc.subject.mesh | Bias (Epidemiology) | en |
dc.subject.mesh | Chromosome Mapping | en |
dc.subject.mesh | Computer Simulation | en |
dc.subject.mesh | Databases, Genetic | en |
dc.subject.mesh | Gene Expression Regulation | en |
dc.subject.mesh | Hematopoietic Stem Cells | en |
dc.subject.mesh | Hippocampus | en |
dc.subject.mesh | Lung | en |
dc.subject.mesh | Mice | en |
dc.subject.mesh | Models, Genetic | en |
dc.subject.mesh | Mutation | en |
dc.subject.mesh | Polymorphism, Single Nucleotide | en |
dc.subject.mesh | Quantitative Trait Loci | en |
dc.subject.mesh | Quantitative Trait, Heritable | en |
dc.subject.mesh | Sample Size | en |
dc.subject.mesh | T-Lymphocytes, Regulatory | en |
dc.title | Data-driven assessment of eQTL mapping methods. | en |
dc.type | Article | en |
dc.contributor.department | Cellular Networks and Systems Biology, Biotechnology Center - TU Dresden, Dresden, Germany. | en |
dc.identifier.journal | BMC genomics | en |
refterms.dateFOA | 2018-06-13T02:30:37Z | |
html.description.abstract | The analysis of expression quantitative trait loci (eQTL) is a potentially powerful way to detect transcriptional regulatory relationships at the genomic scale. However, eQTL data sets often go underexploited because legacy QTL methods are used to map the relationship between the expression trait and genotype. Often these methods are inappropriate for complex traits such as gene expression, particularly in the case of epistasis. |