Skip to main content

Volume 5 Supplement 9

Genetic Analysis Workshop 17: Unraveling Human Exome Data

Proceedings

Edited by S Ghosh, H Bickeböller, J Bailey, JE Bailey-Wilson, R Cantor, W Daw, AL DeStefano, CD Engelman, A Hinrichs, J Houwing-Duistermaat, IR König, J Kent Jr., N Pankratz, A Paterson, E Pugh, Y Sun, A Thomas, N Tintle, X Zhu, JW MacCluer and L Almasy

Genetic Analysis Workshop 17. Go to conference site.

Boston, MA, USA13-16 October 2010

Page 2 of 3

  1. As the cost of sequencing decreases, the demand for association tests that use exhaustive DNA sequence information increases. One such association test is multivariate distance matrix regression (MDMR). We exp...

    Authors: Doyoung Chung, Qunyuan Zhang, Aldi T Kraja, Ingrid B Borecki and Michael A Province
    Citation: BMC Proceedings 2011 5(Suppl 9):S54
  2. Evolutionary genetic models predict that the cumulative effect of rare deleterious mutations across the genome—known as mutational load burden—increases the susceptibility to complex disease. To test the mutat...

    Authors: Daniel P Howrigan, Matthew A Simonson, Helen M Kamens, Sarah H Stephens, Amanda G Wills, Marissa A Ehringer, Matthew C Keller and Matthew B McQueen
    Citation: BMC Proceedings 2011 5(Suppl 9):S55
  3. Genome-wide association studies are a powerful approach used to identify common variants for complex disease. However, the traditional genome-wide association methods may not be optimal when they are applied t...

    Authors: Xin Huang, Yixin Fang and Junhui Wang
    Citation: BMC Proceedings 2011 5(Suppl 9):S56
  4. Genetic association studies usually involve a large number of single-nucleotide polymorphisms (SNPs) (k) and a relative small sample size (n), which produces the situation that k is much greater than n. Because c...

    Authors: Soonil Kwon, Xiaofei Yan, Jinrui Cui, Jie Yao, Kai Yang, Donald Tsiang, Xiaohui Li, Jerome I Rotter and Xiuqing Guo
    Citation: BMC Proceedings 2011 5(Suppl 9):S57
  5. As genetic maps become more highly dense, the ability to sufficiently localize putative disease loci becomes an achievable goal. This has prompted an increased interest in methods for constructing confidence i...

    Authors: Charalampos Papachristou
    Citation: BMC Proceedings 2011 5(Suppl 9):S58
  6. A number of studies have been conducted to investigate the predictive value of common genetic variants for complex diseases. To date, these studies have generally shown that common variants have no appreciable...

    Authors: Chengqing Wu, Kyle M Walsh, Andrew T DeWan, Josephine Hoh and Zuoheng Wang
    Citation: BMC Proceedings 2011 5(Suppl 9):S61
  7. We show that the statistical power of a single single-nucleotide polymorphism (SNP) score test for genetic association reflects the cumulative effect of all causal SNPs that are correlated with the test SNP. S...

    Authors: Yanming Di, Gu Mi, Luna Sun, Rongrong Dong, Hong Zhu and Lili Peng
    Citation: BMC Proceedings 2011 5(Suppl 9):S63
  8. Genome-wide association studies (GWAS) test for disease-trait associations and estimate effect sizes at tag single-nucleotide polymorphisms (SNPs), which imperfectly capture variation at causal SNPs. Sequencin...

    Authors: Laura L Faye and Shelley B Bull
    Citation: BMC Proceedings 2011 5(Suppl 9):S64
  9. Statistical tests on rare variant data may well have type I error rates that differ from their nominal levels. Here, we use the Genetic Analysis Workshop 17 data to estimate type I error rates and powers of th...

    Authors: Jing Jin, Jane E Cerise, Sun Jung Kang, Eun Jung Yoon, Seungtai Yoon, Nancy R Mendell and Stephen J Finch
    Citation: BMC Proceedings 2011 5(Suppl 9):S66
  10. We use a novel penalized approach for genome-wide association study that accounts for the linkage disequilibrium between adjacent markers. This method uses a penalty on the difference of the genetic effect at ...

    Authors: Jin Liu, Kai Wang, Shuangge Ma and Jian Huang
    Citation: BMC Proceedings 2011 5(Suppl 9):S67
  11. Compared to genome-wide association analysis, linkage analysis is less influenced by allelic heterogeneity. The use of linkage information in large families should provide a great opportunity to identify less ...

    Authors: Wei-Min Chen, Ani Manichaikul and Stephen S Rich
    Citation: BMC Proceedings 2011 5(Suppl 9):S68
  12. Genetic Analysis Workshop 17 provided simulated phenotypes and exome sequence data for 697 independent individuals (209 case subjects and 488 control subjects). The disease liability in these data was influenc...

    Authors: Chen Min Lin, Fah J Sathirapongsasuti and Berit Kerner
    Citation: BMC Proceedings 2011 5(Suppl 9):S71
  13. Joint analyses of correlated phenotypes in genetic epidemiology studies are common. However, these analyses primarily focus on genetic correlation between traits and do not take into account environmental corr...

    Authors: Phillip E Melton, Jack W Kent Jr, Thomas D Dyer, Laura Almasy and John Blangero
    Citation: BMC Proceedings 2011 5(Suppl 9):S72
  14. Clinical binary end-point traits are often governed by quantitative precursors. Hence it may be a prudent strategy to analyze a clinical end-point trait by considering a multivariate phenotype vector, possibly...

    Authors: Indranil Mukhopadhyay, Sujayam Saha and Saurabh Ghosh
    Citation: BMC Proceedings 2011 5(Suppl 9):S73
  15. The common genetic variants identified through genome-wide association studies explain only a small proportion of the genetic risk for complex diseases. The advancement of next-generation sequencing technologi...

    Authors: Jingyuan Zhao and Anbupalam Thalamuthu
    Citation: BMC Proceedings 2011 5(Suppl 9):S75
  16. Large-scale, deep resequencing may be the next logical step in the genetic investigation of common complex diseases. Because each individual is likely to carry many thousands of variants, the identification of...

    Authors: Nirmala Akula, Sevilla Detera-Wadleigh, Yin Yao Shugart, Michael Nalls, Jo Steele and Francis J McMahon
    Citation: BMC Proceedings 2011 5(Suppl 9):S76
  17. Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicat...

    Authors: Marcio Augusto Alfonso de Almeida, Andrea Roseli Vançan Russo Horimoto, Paulo Sérgio Lopes de Oliveira, José Eduardo Krieger and Alexandre da Costa Pereira
    Citation: BMC Proceedings 2011 5(Suppl 9):S78
  18. To date, genome-wide association studies have yielded discoveries of common variants that partly explain familial aggregation of diseases and traits. Researchers are now turning their attention to less common ...

    Authors: Seung-Hoan Choi, Chunyu Liu, Josée Dupuis, Mark W Logue and Gyungah Jun
    Citation: BMC Proceedings 2011 5(Suppl 9):S79
  19. We report two approaches for linkage analysis of data consisting of replicate phenotypes. The first approach is specifically designed for the unusual (in human data) replicate structure of the Genetic Analysis...

    Authors: Anthony L Hinrichs, Robert C Culverhouse and Brian K Suarez
    Citation: BMC Proceedings 2011 5(Suppl 9):S81
  20. Genome-wide association studies have been successful in identifying common variants for common complex traits in recent years. However, common variants have generally failed to explain substantial proportions ...

    Authors: Gang Shi, Jeannette Simino and Dabeeru C Rao
    Citation: BMC Proceedings 2011 5(Suppl 9):S82
  21. Family-based study designs are again becoming popular as new next-generation sequencing technologies make whole-exome and whole-genome sequencing projects economically and temporally feasible. Here we evaluate...

    Authors: Claire L Simpson, Cristina M Justice, Mera Krishnan, Robert Wojciechowski, Heejong Sung, Jerry Cai, Tiffany Green, Deyana Lewis, Dana Behneman, Alexander F Wilson and Joan E Bailey-Wilson
    Citation: BMC Proceedings 2011 5(Suppl 9):S83
  22. We evaluate an approach to detect single-nucleotide polymorphisms (SNPs) that account for a linkage signal with covariate-based affected relative pair linkage analysis in a conditional-logistic model framework...

    Authors: Yeunjoo E Song, Junghyun Namkung, Robert W Shields, Daniel J Baechle, Sunah Song and Robert C Elston
    Citation: BMC Proceedings 2011 5(Suppl 9):S84
  23. How various genetic effects in combination affect susceptibility to certain disease states continues to be a major area of methodological research. Various rare variant models have been proposed, in response t...

    Authors: Lu Cheng, Pingzhao Hu, Jenna Sykes, Melania Pintilie, Geoffrey Liu and Wei Xu
    Citation: BMC Proceedings 2011 5(Suppl 9):S85
  24. We evaluate four association tests for rare variants—the combined multivariate and collapsing (CMC) method, two weighted-sum methods, and a variable threshold method—by applying them to the simulated data sets...

    Authors: Wenan Chen, Xi Gao, Jiexun Wang, Chuanyu Sun, Wen Wan, Degui Zhi, Nianjun Liu, Xiangning Chen and Guimin Gao
    Citation: BMC Proceedings 2011 5(Suppl 9):S86
  25. The synthetic association hypothesis proposes that common genetic variants detectable in genome-wide association studies may reflect the net phenotypic effect of multiple rare polymorphisms distributed broadly...

    Authors: Jack W Kent Jr, Vidya Farook, Harald HH Göring, Thomas D Dyer, Laura Almasy, Ravindranath Duggirala and John Blangero
    Citation: BMC Proceedings 2011 5(Suppl 9):S87
  26. Genome-wide association studies are based on the linkage disequilibrium pattern between common tagging single-nucleotide polymorphisms (SNPs) (i.e., SNPs having only common alleles) and true causal variants, a...

    Authors: Xiangqing Sun, Junghyun Namkung, Xiaofeng Zhu and Robert C Elston
    Citation: BMC Proceedings 2011 5(Suppl 9):S88
  27. Genome-wide association studies have helped us identify thousands of common variants associated with several widespread complex diseases. However, for most traits, these variants account for only a small fract...

    Authors: Anbupalam Thalamuthu, Jingyuan Zhao, Garrett Teoh Hor Keong, Venkateswarlu Kondragunta and Indranil Mukhopadhyay
    Citation: BMC Proceedings 2011 5(Suppl 9):S89
  28. Testing for association between multiple markers and a phenotype can not only capture untyped causal variants in weak linkage disequilibrium with nearby typed markers but also identify the effect of a combinat...

    Authors: Kristin L Ayers, Chrysovalanto Mamasoula and Heather J Cordell
    Citation: BMC Proceedings 2011 5(Suppl 9):S92
  29. Next-generation sequencing technologies are rapidly changing the field of genetic epidemiology and enabling exploration of the full allele frequency spectrum underlying complex diseases. Although sequencing te...

    Authors: Julio S Bueno Filho, Gota Morota, Quoc Tran, Matthew J Maenner, Lina M Vera-Cala, Corinne D Engelman and Kristin J Meyers
    Citation: BMC Proceedings 2011 5(Suppl 9):S93
  30. In addition to methods that can identify common variants associated with susceptibility to common diseases, there has been increasing interest in approaches that can identify rare genetic variants. We use the ...

    Authors: Yauheniya Cherkas, Nandini Raghavan, Stephan Francke, Frank DeFalco and Marsha A Wilcox
    Citation: BMC Proceedings 2011 5(Suppl 9):S94
  31. We present an evaluation of discovery power for two association tests that work well with common alleles but are applied to the Genetic Analysis Workshop 17 simulations with rare causative single-nucleotide po...

    Authors: Aldi T Kraja, Jacek Czajkowski, Mary F Feitosa, Ingrid B Borecki and Michael A Province
    Citation: BMC Proceedings 2011 5(Suppl 9):S96
  32. The upcoming release of new whole-genome genotyping technologies will shed new light on whether there is an associative effect of previously immeasurable rare variants on incidence of disease. For Genetic Anal...

    Authors: Jenna Sykes, Lu Cheng, Wei Xu, Ming-Sound Tsao, Geoffrey Liu and Melania Pintilie
    Citation: BMC Proceedings 2011 5(Suppl 9):S97
  33. We present a new statistical method to identify genes in which one or more variants influence quantitative traits. We use the Genetic Analysis Workshop 17 (GAW17) data set of unrelated individuals as a test of...

    Authors: Ian J Wilson, Richard AJ Howey, Darren T Houniet and Mauro Santibanez-Koref
    Citation: BMC Proceedings 2011 5(Suppl 9):S98
  34. Recent advances in next-generation sequencing technologies have made it possible to generate large amounts of sequence data with rare variants in a cost-effective way. Statistical methods that test variants in...

    Authors: Aimin Yan, Nan M Laird and Cheng Li
    Citation: BMC Proceedings 2011 5(Suppl 9):S99
  35. Genetic markers with rare variants are spread out in the genome, making it necessary and difficult to consider them in genetic association studies. Consequently, wisely combining rare variants into “composite”...

    Authors: Jennifer S Brennan, Yunxiao He, Rose Calixte, Epiphanie Nyirabahizi, Yuan Jiang and Heping Zhang
    Citation: BMC Proceedings 2011 5(Suppl 9):S100

Annual Journal Metrics

  • 2022 Citation Impact
    0.914 - SNIP (Source Normalized Impact per Paper)
    0.506 - SJR (SCImago Journal Rank)

    2022 Usage 
    575,965 downloads
    477 Altmetric mentions