Comprehensive Approach to Analyzing Rare Genetic Variants
Author
Abstract
Suggested Citation
DOI: 10.1371/journal.pone.0013584
Download full text from publisher
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Timothy D O’Connor & Adam Kiezun & Michael Bamshad & Stephen S Rich & Joshua D Smith & Emily Turner & NHLBIGO Exome Sequencing Project & ESP Population Genetics, Statistical Analysis Working Group & S, 2013. "Fine-Scale Patterns of Population Stratification Confound Rare Variant Association Tests," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-10, July.
- Gourab De & Wai-Ki Yip & Iuliana Ionita-Laza & Nan Laird, 2013. "Rare Variant Analysis for Family-Based Design," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-9, January.
- Rajesh Talluri & Sanjay Shete, 2013. "A Linkage Disequilibrium–Based Approach to Selecting Disease-Associated Rare Variants," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-6, July.
- Rachel Marceau West & Wenbin Lu & Daniel M Rotroff & Melaine A Kuenemann & Sheng-Mao Chang & Michael C Wu & Michael J Wagner & John B Buse & Alison A Motsinger-Reif & Denis Fourches & Jung-Ying Tzeng, 2019. "Identifying individual risk rare variants using protein structure guided local tests (POINT)," PLOS Computational Biology, Public Library of Science, vol. 15(2), pages 1-24, February.
- Daniel D Kinnamon & Ray E Hershberger & Eden R Martin, 2012. "Reconsidering Association Testing Methods Using Single-Variant Test Statistics as Alternatives to Pooling Tests for Sequence Data with Rare Variants," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-15, February.
- Yi Nengjun & Xu Shizhong & Lou Xiang-Yang & Mallick Himel, 2014. "Multiple comparisons in genetic association studies: a hierarchical modeling approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(1), pages 35-48, February.
- Nanye Long & Samuel P Dickson & Jessica M Maia & Hee Shin Kim & Qianqian Zhu & Andrew S Allen, 2013. "Leveraging Prior Information to Detect Causal Variants via Multi-Variant Regression," PLOS Computational Biology, Public Library of Science, vol. 9(6), pages 1-11, June.
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:plo:pone00:0013584. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.