IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v437y2005i7063d10.1038_nature04244.html
   My bibliography  Save this article

Mapping determinants of human gene expression by regional and genome-wide association

Author

Listed:
  • Vivian G. Cheung

    (University of Pennsylvania
    University of Pennsylvania
    The Children's Hospital of Philadelphia)

  • Richard S. Spielman

    (University of Pennsylvania)

  • Kathryn G. Ewens

    (University of Pennsylvania)

  • Teresa M. Weber

    (University of Pennsylvania
    The Children's Hospital of Philadelphia)

  • Michael Morley

    (The Children's Hospital of Philadelphia)

  • Joshua T. Burdick

    (The Children's Hospital of Philadelphia)

Abstract

Self expression Even when two humans have the same genes, the levels at which those genes are expressed can contribute greatly to variation between individuals. Based on HapMap Project data, Cheung et al. use genetic association to map the parts of each gene that control levels of expression. The data also provide a detailed comparison of the techniques of genetic linkage and association, both of which are used to look for genetic determinants of human disease.

Suggested Citation

  • Vivian G. Cheung & Richard S. Spielman & Kathryn G. Ewens & Teresa M. Weber & Michael Morley & Joshua T. Burdick, 2005. "Mapping determinants of human gene expression by regional and genome-wide association," Nature, Nature, vol. 437(7063), pages 1365-1369, October.
    • Handle: RePEc:nat:nature:v:437:y:2005:i:7063:d:10.1038_nature04244
    DOI: 10.1038/nature04244
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature04244
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/nature04244?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Heather E Wheeler & Kaanan P Shah & Jonathon Brenner & Tzintzuni Garcia & Keston Aquino-Michaels & GTEx Consortium & Nancy J Cox & Dan L Nicolae & Hae Kyung Im, 2016. "Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues," PLOS Genetics, Public Library of Science, vol. 12(11), pages 1-23, November.
    2. Yixin Fang & Yang Feng & Ming Yuan, 2014. "Regularized principal components of heritability," Computational Statistics, Springer, vol. 29(3), pages 455-465, June.
    3. Barbara E Stranger & Stephen B Montgomery & Antigone S Dimas & Leopold Parts & Oliver Stegle & Catherine E Ingle & Magda Sekowska & George Davey Smith & David Evans & Maria Gutierrez-Arcelus & Alkes P, 2012. "Patterns of Cis Regulatory Variation in Diverse Human Populations," PLOS Genetics, Public Library of Science, vol. 8(4), pages 1-13, April.
    4. Ning Jiang & Minghui Wang & Tianye Jia & Lin Wang & Lindsey Leach & Christine Hackett & David Marshall & Zewei Luo, 2011. "A Robust Statistical Method for Association-Based eQTL Analysis," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-11, August.
    5. Ryan Abo & Gregory D Jenkins & Liewei Wang & Brooke L Fridley, 2012. "Identifying the Genetic Variation of Gene Expression Using Gene Sets: Application of Novel Gene Set eQTL Approach to PharmGKB and KEGG," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-11, August.
    6. Paul C Boutros & Ivy D Moffat & Allan B Okey & Raimo Pohjanvirta, 2011. "mRNA Levels in Control Rat Liver Display Strain-Specific, Hereditary, and AHR-Dependent Components," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-15, July.
    7. Jae Hoon Sul & Buhm Han & Chun Ye & Ted Choi & Eleazar Eskin, 2013. "Effectively Identifying eQTLs from Multiple Tissues by Combining Mixed Model and Meta-analytic Approaches," PLOS Genetics, Public Library of Science, vol. 9(6), pages 1-13, June.
    8. Jin Hyun Ju & Sushila A Shenoy & Ronald G Crystal & Jason G Mezey, 2017. "An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci," PLOS Computational Biology, Public Library of Science, vol. 13(5), pages 1-26, May.
    9. Josine L Min & Jennifer M Taylor & J Brent Richards & Tim Watts & Fredrik H Pettersson & John Broxholme & Kourosh R Ahmadi & Gabriela L Surdulescu & Ernesto Lowy & Christian Gieger & Chris Newton-Cheh, 2011. "The Use of Genome-Wide eQTL Associations in Lymphoblastoid Cell Lines to Identify Novel Genetic Pathways Involved in Complex Traits," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-14, July.
    10. Alexandra C Nica & Leopold Parts & Daniel Glass & James Nisbet & Amy Barrett & Magdalena Sekowska & Mary Travers & Simon Potter & Elin Grundberg & Kerrin Small & Åsa K Hedman & Veronique Bataille & Jo, 2011. "The Architecture of Gene Regulatory Variation across Multiple Human Tissues: The MuTHER Study," PLOS Genetics, Public Library of Science, vol. 7(2), pages 1-9, February.
    11. David M Evans & Marie Jo A Brion & Lavinia Paternoster & John P Kemp & George McMahon & Marcus Munafò & John B Whitfield & Sarah E Medland & Grant W Montgomery & The GIANT consortium & The CRP consort, 2013. "Mining the Human Phenome Using Allelic Scores That Index Biological Intermediates," PLOS Genetics, Public Library of Science, vol. 9(10), pages 1-15, October.
    12. Hui-Min Wang & Ching-Lin Hsiao & Ai-Ru Hsieh & Ying-Chao Lin & Cathy S J Fann, 2012. "Constructing Endophenotypes of Complex Diseases Using Non-Negative Matrix Factorization and Adjusted Rand Index," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-12, July.
    13. Rudi Alberts & Peter Terpstra & Yang Li & Rainer Breitling & Jan-Peter Nap & Ritsert C Jansen, 2007. "Sequence Polymorphisms Cause Many False cis eQTLs," PLOS ONE, Public Library of Science, vol. 2(7), pages 1-5, July.
    14. Daria V Zhernakova & Eleonora de Klerk & Harm-Jan Westra & Anastasios Mastrokolias & Shoaib Amini & Yavuz Ariyurek & Rick Jansen & Brenda W Penninx & Jouke J Hottenga & Gonneke Willemsen & Eco J de Ge, 2013. "DeepSAGE Reveals Genetic Variants Associated with Alternative Polyadenylation and Expression of Coding and Non-coding Transcripts," PLOS Genetics, Public Library of Science, vol. 9(6), pages 1-15, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:437:y:2005:i:7063:d:10.1038_nature04244. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.