Comparison of results from tests of association in unrelated individuals with uncollapsed and collapsed sequence variants using tiled regression

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• 作者：Heejong Sung (1)
  Yoonhee Kim (1)
  Juanliang Cai (1)
  Cheryl D Cropp (2)
  Claire L Simpson (2)
  Qing Li (2)
  Brian C Perry (2)
  Alexa JM Sorant (1)
  Joan E Bailey-Wilson (2)
  Alexander F Wilson (1)
  
• 刊名：BMC Proceedings
• 出版年：2011
• 出版时间：December 2011
• 年：2011
• 卷：5
• 期：9-supp
• 全文大小：158KB
• 参考文献：1. Wilson AF, Kim Y, Sung H, Cai J, McMahon FJ, Sorant AJM: Tiled regression: the use of regression methods in hotspot defined genomic segments to identify independent genetic variants responsible for variation in quantitative traits. / International Genetic Epidemiology Society, 18th Annual Meeting 2009. Abstract 142 http://www.geneticepi.org/meetings/2009 in Abstracts.doc
  2. Patterson N, Prics AL, Reich D: Population structure and Eigenanalysis. / PLoS Genet 2006, 2:190. CrossRef
  3. Li B, Leal SM: Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. / Am J Hum Genet 2008,83(3):311鈥?21. CrossRef
  4. Dering C, Pugh E, Ziegler A: Statistical analysis of rare sequence variants: an overview of collapsing methods. / Genet Epidemiol 2011,35(8):12鈥?7. CrossRef
  5. Sorant AJM, Cai J, Sung H, Kim Y, Wilson AF: / Tiled Regression Analysis Package (TRAP): software implementation of tiled regression methodology. International Genetic Epidemiology Society, 19th Annual Meeting; 2010.
  6. Human Genome Sequence Build 36 [http://www.stats.ox.ac.uk/~mcvean/OXSTAT/GeneticMap_b36]
  7. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, / et al.: PLINK: a tool set for whole-genome association and population-based linkage analysis. / Am J Hum Genet 2007, 81:559鈥?75. CrossRef
  8. Almasy LA, Dyer TD, Peralta JM, Kent JW Jr, Charlesworth JC, Curran JE, Blangero J: Genetic Analysis Workshop 17 mini-exome simulation. / BMC Proc 2011,5(Suppl 9):S2. CrossRef
  
• 作者单位：Heejong Sung (1)
  Yoonhee Kim (1)
  Juanliang Cai (1)
  Cheryl D Cropp (2)
  Claire L Simpson (2)
  Qing Li (2)
  Brian C Perry (2)
  Alexa JM Sorant (1)
  Joan E Bailey-Wilson (2)
  Alexander F Wilson (1)
  
  1. Genometrics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive, Baltimore, MD, 21224, USA
  2. Statistical Genetics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive, Baltimore, MD, 21224, USA
  

文摘

Tiled regression is an approach designed to determine the set of independent genetic variants that contribute to the variation of a quantitative trait in the presence of many highly correlated variants. In this study, we evaluate the statistical properties of the tiled regression method using the Genetic Analysis Workshop 17 data in unrelated individuals for traits Q1, Q2, and Q4. To increase the power to detect rare variants, we use two methods to collapse rare variants and compare the results with those from the uncollapsed data. In addition, we compare the tiled regression method to traditional tests of association with and without collapsed rare variants. The results show that collapsing rare variants generally improves the power to detect associations regardless of method, although only variants with the largest allelic effects could be detected. However, for traditional simple linear regression, the average estimated type I error is dependent on the trait and varies by about three orders of magnitude. The estimated type I error rate is stable for tiled regression across traits.