Genetic analysis of genome-wide variation in human gene expression

By M. Morley, C. Molony, Teresa M. Weber, James L. Devlin, K. Ewens, R. Spielman, V. Cheung. Nature, 2004

1,281 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2459b8e56f02c9d9c3b19ae8fcd75fedf05391d5

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Citations in the corpus

Mapping the Genetic Architecture of Gene Expression in Human Liver (2008, background): “The relatively large sample size of this study and the large number of SNPs genotyped provided the means to assess the relationship between genetic variants and gene expression with more statistical power than many previous studies allowed [11–13].”
A unified mixed-model method for association mapping that accounts for multiple levels of relatedness (2006, methodology): “For the family-based sample, we applied our method to microarray data from the baseline expression levels of genes in immortalized B cells from 14 families of Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigre”
Genome-wide association studies: theoretical and practical concerns (2005, background): “— which is likely to have smaller effects than polymorphisms that affect the coding sequence — and that loci with alleles that affect the regulation of gene expression can be detected by linkage analyse”
Family-based association tests for genomewide association scans. (2007, methodology): “As a complement to the simulation studies presented above, we reanalyzed publicly available data for 27 geneexpression traits.(32,33) The data consist of gene-expression measurements for 156 individuals in 20 3-generation CEPH pedigrees, each with 12–17 individuals.”
Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network (2009, methodology): “…and molecular analysis of diseases were mainly based on classical statistical techniques, such as the linkage analysis of selected markers [3,4]; quantitative trait locus (QTL) mapping [5,6] conducted over one phenotype and one marker genotype at a time, which are then corrected for…”
Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis (2007, background): “Specific genetic loci have been shown to influence the expression of hundreds or thousands of genes in several organisms [10,11,15].”
Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. (2006, background): “However, it has turned out that, in most genes, differences in expression are determined by genetic variation in genes located elsewhere.(55,56) The reconstructed functional gene network can help to relate the observed differences in gene expression to the underlying causative genetic variants in ot”
Retrotransposons revisited: the restraint and rehabilitation of parasites. (2008, positive): “Morley et al. (2004) assayed CEPH cell lines from 14 pedigrees and found 3554 genes that varied in expression levels.”
Temporal dynamics and genetic control of transcription in the human prefrontal cortex (2011, background): “ppt"/> Previous investigations have combined transcriptional and genetic analyses in human cell line”
Molecular networks as sensors and drivers of common human diseases (2009, background): “In fact, the advances made in mapping DNA loci for diseases have occurred simultaneously with the mapping of DNA loci for molecular traits such as transcript abundance”