IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v68y2012i1p1-11.html
   My bibliography  Save this article

A Statistical Framework for eQTL Mapping Using RNA-seq Data

Author

Listed:
  • Wei Sun

Abstract

No abstract is available for this item.

Suggested Citation

  • Wei Sun, 2012. "A Statistical Framework for eQTL Mapping Using RNA-seq Data," Biometrics, The International Biometric Society, vol. 68(1), pages 1-11, March.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:1:p:1-11
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01654.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    References listed on IDEAS

    as
    1. C. M. Kendziorski & M. Chen & M. Yuan & H. Lan & A. D. Attie, 2006. "Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping," Biometrics, The International Biometric Society, vol. 62(1), pages 19-27, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Abbas Khalili & Shili Lin, 2013. "Regularization in Finite Mixture of Regression Models with Diverging Number of Parameters," Biometrics, The International Biometric Society, vol. 69(2), pages 436-446, June.
    2. Paul Little & Si Liu & Vasyl Zhabotynsky & Yun Li & Dan-Yu Lin & Wei Sun, 2023. "A computational method for cell type-specific expression quantitative trait loci mapping using bulk RNA-seq data," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Chuan Hong & Yang Ning & Peng Wei & Ying Cao & Yong Chen, 2017. "A semiparametric model for vQTL mapping," Biometrics, The International Biometric Society, vol. 73(2), pages 571-581, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bo Jiang & Jun S. Liu, 2015. "Bayesian Partition Models for Identifying Expression Quantitative Trait Loci," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1350-1361, December.
    2. Enrico Petretto & Leonardo Bottolo & Sarah R Langley & Matthias Heinig & Chris McDermott-Roe & Rizwan Sarwar & Michal Pravenec & Norbert Hübner & Timothy J Aitman & Stuart A Cook & Sylvia Richardson, 2010. "New Insights into the Genetic Control of Gene Expression using a Bayesian Multi-tissue Approach," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-13, April.
    3. Jonathan A. L. Gelfond & Joseph G. Ibrahim & Fei Zou, 2007. "Proximity Model for Expression Quantitative Trait Loci (eQTL) Detection," Biometrics, The International Biometric Society, vol. 63(4), pages 1108-1116, December.
    4. Chang, Yu-Ling & Zou, Fei & Wright, Fred A., 2010. "An approximate Bayesian approach for quantitative trait loci estimation," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 565-574, February.
    5. Chaturvedi Nimisha & Menezes Renée X. de & Goeman Jelle J. & Wieringen Wessel van, 2018. "A test for detecting differential indirect trans effects between two groups of samples," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 17(5), pages 1-11, October.
    6. Anindya Bhadra & Bani K. Mallick, 2013. "Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis," Biometrics, The International Biometric Society, vol. 69(2), pages 447-457, June.
    7. Wei Zhang & Jun Zhu & Eric E Schadt & Jun S Liu, 2010. "A Bayesian Partition Method for Detecting Pleiotropic and Epistatic eQTL Modules," PLOS Computational Biology, Public Library of Science, vol. 6(1), pages 1-10, January.
    8. Brown Andrew Anand & Richardson Sylvia & Whittaker John, 2011. "Application of the Lasso to Expression Quantitative Trait Loci Mapping," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-35, March.

    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:bla:biomet:v:68:y:2012:i:1:p:1-11. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.