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Volume 1 Supplement 1

Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci

Proceedings

Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci. Go to conference site.

St. Pete Beach, Florida, USA11-15 November 2006

Page 2 of 4

  1. Several genetic determinants responsible for individual variation in gene expression have been located using linkage and association analyses. These analyses have revealed regulatory relationships between gene...

    Authors: Robert Yu, Kevin DeHoff, Christopher I Amos and Sanjay Shete
    Citation: BMC Proceedings 2007 1(Suppl 1):S51
  2. The Genetic Analysis Workshop 15 (GAW15) Problem 1 contained baseline expression levels of 8793 genes in immortalized B cells from 194 individuals in 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedig...

    Authors: Jing Hua Zhao, Jian'an Luan, M Fazil Baksh and Qihua Tan
    Citation: BMC Proceedings 2007 1(Suppl 1):S52
  3. Genomic imprinting is a mechanism in which the expression of a gene copy depends upon the sex of the parent from which it was inherited. This mechanism is now well recognized in humans, and the deregulation of...

    Authors: Xiaojun Zhou, Wei Chen, Michael D Swartz, Yue Lu, Robert Yu, Christopher I Amos, Chih-Chieh Wu and Sanjay Shete
    Citation: BMC Proceedings 2007 1(Suppl 1):S53
  4. Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid ...

    Authors: Beate Glaser, Ivan Nikolov, Daniel Chubb, Marian L Hamshere, Ricardo Segurado, Valentina Moskvina and Peter Holmans
    Citation: BMC Proceedings 2007 1(Suppl 1):S54
  5. We used the simulated data set from Genetic Analysis Workshop 15 Problem 3 to assess a two-stage approach for identifying single-nucleotide polymorphisms (SNPs) associated with rheumatoid arthritis (RA). In th...

    Authors: Yan Meng, Qiong Yang, Karen T Cuenco, L Adrienne Cupples, Anita L DeStefano and Kathryn L Lunetta
    Citation: BMC Proceedings 2007 1(Suppl 1):S56
  6. Risk of complex disorders is thought to be multifactorial, involving interactions between risk factors. However, many genetic studies assess association between disease status and markers one single-nucleotide...

    Authors: Kristin K Nicodemus, Wenyi Wang and Yin Yao Shugart
    Citation: BMC Proceedings 2007 1(Suppl 1):S58
  7. With the development of high-throughput single-nucleotide polymorphism (SNP) technologies, the vast number of SNPs in smaller samples poses a challenge to the application of classical statistical procedures. A...

    Authors: Daniel F Schwarz, Silke Szymczak, Andreas Ziegler and Inke R Kƶnig
    Citation: BMC Proceedings 2007 1(Suppl 1):S59
  8. The Genetic Analysis Workshop 15 Problem 3 simulated rheumatoid arthritis data set provided 100 replicates of simulated single-nucleotide polymorphism (SNP) and covariate data sets for 1500 families with an af...

    Authors: Weiliang Shi, Kristine E Lee and Grace Wahba
    Citation: BMC Proceedings 2007 1(Suppl 1):S60
  9. Significant alterations of T-cell function, along with activation of the inflammatory response system, appear to be linked not only to treatment-resistant schizophrenia, but also to functional psychoses and mo...

    Authors: Hans H Stassen, Armin Szegedi and Christian Scharfetter
    Citation: BMC Proceedings 2007 1(Suppl 1):S61
  10. Using the North American Rheumatoid Arthritis Consortium (NARAC) candidate gene and genome-wide single-nucleotide polymorphism (SNP) data sets, we applied regression methods and tree-based random forests to id...

    Authors: Yan V Sun, Zhaohui Cai, Kaushal Desai, Rachael Lawrance, Richard Leff, Ansar Jawaid, Sharon LR Kardia and Huiying Yang
    Citation: BMC Proceedings 2007 1(Suppl 1):S62
  11. When two genes interact to cause a clinically important phenotype, it would seem reasonable to expect that we could leverage genotypic information at one of the loci in order to improve our ability to detect t...

    Authors: Yungui Huang, Christopher W Bartlett, Alberto M Segre, Jeffrey R O'Connell, LaVonne Mangin and Veronica J Vieland
    Citation: BMC Proceedings 2007 1(Suppl 1):S64
  12. Non-parametric linkage methods have had limited success in detecting gene by gene interactions. Using affected sibling-pair (ASP) data from all replicates of the simulated data from Problem 3, we assessed the ...

    Authors: Emma K Larkin, Nathan J Morris, Yali Li, Nora L Nock and Catherine M Stein
    Citation: BMC Proceedings 2007 1(Suppl 1):S66
  13. It is believed that epistatic interactions among loci contribute to variations in quantitative traits. Several methods are available to detect epistasis using population-based data. However, methods to charact...

    Authors: Hua Li, Guimin Gao, Jian Li, Grier P Page and Kui Zhang
    Citation: BMC Proceedings 2007 1(Suppl 1):S67
  14. Rheumatoid arthritis (RA) is a multifactorial disease with complex genetic etiology, about which little is known. Here, we apply a two-stage procedure in which a quick first-stage analysis was used to narrow d...

    Authors: Nandita Mukhopadhyay, Indrani Halder, Samsiddhi Bhattacharjee and Daniel E Weeks
    Citation: BMC Proceedings 2007 1(Suppl 1):S68
  15. Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient an...

    Authors: Junghyun Namkung, Jin-Wu Nam and Taesung Park
    Citation: BMC Proceedings 2007 1(Suppl 1):S69
  16. The identification of susceptibility genes for common, chronic disease presents great challenges. The development of novel statistical and computational methodologies to help identify these genes is an area of...

    Authors: Marylyn D Ritchie, Jacquelaine Bartlett, William S Bush, Todd L Edwards, Alison A Motsinger and Eric S Torstenson
    Citation: BMC Proceedings 2007 1(Suppl 1):S70
  17. Accounting for interactions with environmental factors in association studies may improve the power to detect genetic effects and may help identifying important environmental effect modifiers. The power of unp...

    Authors: Astrid Dempfle, Rebecca Hein, Lars Beckmann, AndrƩ Scherag, Thuy Trang Nguyen, Helmut SchƤfer and Jenny Chang-Claude
    Citation: BMC Proceedings 2007 1(Suppl 1):S73
  18. Identifying gene-environment (G Ɨ E) interactions has become a crucial issue in the past decades. Different methods have been proposed to test for G Ɨ E interactions in the framework of linkage or association ...

    Authors: RĆ©mi Kazma, Marie-HĆ©lĆØne Dizier, Michel Guilloud-Bataille, Catherine BonaĆÆti-PelliĆ© and Emmanuelle GĆ©nin
    Citation: BMC Proceedings 2007 1(Suppl 1):S74
  19. We incorporate population effects of sex and antibodies directed against cyclic citrullinated peptides (anti-CCP) into the linkage analysis of rheumatoid arthritis (RA) with microsatellites data provided by th...

    Authors: JƩrƩmie JP Lebrec, Quinta Helmer, Iryna Nishchenko and Hans C van Houwelingen
    Citation: BMC Proceedings 2007 1(Suppl 1):S75
  20. Understanding the genetic basis of human variation is an important goal of biomedical research. In this study, we used structural equation models (SEMs) to construct genetic networks to model how specific sing...

    Authors: Seungmook Lee, Mina Jhun, Eun-Kyung Lee and Taesung Park
    Citation: BMC Proceedings 2007 1(Suppl 1):S76
  21. Clinical heterogeneity of a disease may reflect an underlying genetic heterogeneity, which may hinder the detection of trait loci. Consequently, many statistical methods have been developed that allow for the ...

    Authors: HervƩ Perdry, Brion S Maher, Marie-Claude Babron, Toby McHenry, FranƧoise Clerget-Darpoux and Mary L Marazita
    Citation: BMC Proceedings 2007 1(Suppl 1):S77
  22. Focusing on chromosome 1, a recursive partitioning linkage algorithm (RP) was applied to perform linkage analysis on the rheumatoid arthritis NARAC data, incorporating covariates such as HLA-DRB1 genotype, age...

    Authors: Wei Xu, Hui Lan, Pingzhao Hu, Shelley B Bull and Celia MT Greenwood
    Citation: BMC Proceedings 2007 1(Suppl 1):S78
  23. The goal of this paper is to investigate the effect of using principal components as a data reduction method for expression data in linkage analysis. We used 45 probes normalized using the Affymetrix Global Sc...

    Authors: Elizabeth J Atkinson, Brooke L Fridley, Ellen L Goode, Shannon K McDonnell, Wen Liu-Mares, Kari G Rabe, Zhifu Sun, Susan L Slager and Mariza de Andrade
    Citation: BMC Proceedings 2007 1(Suppl 1):S79
  24. Heterogeneity poses a challenge to linkage mapping. Here, we apply a latent class extension of Haseman-Elston regression to expression phenotypes with significant evidence of linkage to trans regulators in 14 lar...

    Authors: Laurel A Bastone, Mary E Putt, Thomas R Ten Have, Vivian G Cheung and Richard S Spielman
    Citation: BMC Proceedings 2007 1(Suppl 1):S80
  25. Microarray technologies allow the measurement of the expression levels of thousands of transcripts at the same time. As part of Genetic Analysis Workshop 15 (GAW15), we analyzed a data set that measured the ex...

    Authors: Alfonso Buil, Alexandre Perera-Lluna, Ramon Souto, Juan M Peralta, Laura Almasy, Montserrat Vallverdu, Pere Caminal and Jose M Soria
    Citation: BMC Proceedings 2007 1(Suppl 1):S81
  26. The genetic factors underlying many complex traits are not well understood. The Genetic Analysis Workshop 15 Problem 1 data present the opportunity to explore whether gene expression data from microarrays can ...

    Authors: G Bryce Christensen, Lisa A Cannon-Albright, Alun Thomas and Nicola J Camp
    Citation: BMC Proceedings 2007 1(Suppl 1):S82
  27. In order to identify regulatory genes, we determined the heritability of gene transcripts, performed linkage analysis to identify quantitative trait loci (QTLs), and evaluated the evidence for shared genetic e...

    Authors: Nora Franceschini, Mary K Wojczynski, Harald HH Gƶring, Juan Manuel Peralta, Thomas D Dyer, Xia Li, Hao Li and Kari E North
    Citation: BMC Proceedings 2007 1(Suppl 1):S85
  28. Recently, gene expression levels have been shown to demonstrate familial aggregation, suggesting a direct role of heritable DNA variation. We studied the gene expression levels in lymphoblastoid cells of the C...

    Authors: Donghui Kan, Richard Cooper and Xiaofeng Zhu
    Citation: BMC Proceedings 2007 1(Suppl 1):S87
  29. We used the Genetic Analysis Workshop 15 Problem 1 data set to search for expression phenotype quantitative trait loci in a highly selected group of genes with a supposedly correlated role in the development o...

    Authors: Francesca Lantieri, Halfdan Rydbeck, Paola Griseri, Isabella Ceccherini and Marcella Devoto
    Citation: BMC Proceedings 2007 1(Suppl 1):S89
  30. A new method for constructing confidence intervals for the location of putative genes regulating expression levels (quantitative traits) is proposed. This method is suitable for the "intermediate" fine-mapping...

    Authors: Charalampos Papachristou, Mark Abney and Shili Lin
    Citation: BMC Proceedings 2007 1(Suppl 1):S91
  31. We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results fo...

    Authors: Yun Ju Sung, Yanming Di, Audrey Q Fu, Joseph H Rothstein, Weiva Sieh, Liping Tong, Elizabeth A Thompson and Ellen M Wijsman
    Citation: BMC Proceedings 2007 1(Suppl 1):S93
  32. Transcription activity 'hot spots', defined as chromosome regions that contain more expression quantitative trait loci than would have been expected by chance, have been frequently detected both in humans and ...

    Authors: Shuang Wang, Tian Zheng and Yuanjia Wang
    Citation: BMC Proceedings 2007 1(Suppl 1):S94
  33. The COMT and DBH genes are physically located at chromosomes 22q11 and 9q34, respectively, and both COMT and DBH are involved in catecholamine metabolism and are strong candidates for certain psychiatric and neur...

    Authors: Chao Xing, Monica Torres-Caban, Tao Wang, Qing Lu, Guan Xing and Robert C Elston
    Citation: BMC Proceedings 2007 1(Suppl 1):S95
  34. Genome scan meta-analysis (GSMA) can prove very useful in detecting genetic effects too small to be detected in an individual linkage study and can also lead to more consistent results. In this paper, we propo...

    Authors: Laurent Briollais, Gilles Durrieu and Ranodya Upathilake
    Citation: BMC Proceedings 2007 1(Suppl 1):S96
  35. We performed linkage analysis on families with rheumatoid arthritis, stratifying by ethnic origin. We compared results using either Kong and Cox nonparametric LOD scores or MOD score analysis using the softwar...

    Authors: Wei V Chen, Christopher I Amos, Carol J Etzel, Sanjay Shete and Peter K Gregersen
    Citation: BMC Proceedings 2007 1(Suppl 1):S97
  36. Rheumatoid arthritis is a complex disease in which environmental factors interact with genetic factors that influence susceptibility. Incorporating information about related quantitative traits or environmenta...

    Authors: Yen-Feng Chiu, Jeng-Min Chiou, Yi-Shin Chen, Hui-Yi Kao and Fang-Chi Hsu
    Citation: BMC Proceedings 2007 1(Suppl 1):S98
  37. Parametric linkage methods for quantitative trait locus mapping require explicit specification of the probability model of the quantitative trait and hence can lead to misleading linkage inferences when the mo...

    Authors: Saurabh Ghosh, P Samba Siva Rao, Gourab De and Partha P Majumder
    Citation: BMC Proceedings 2007 1(Suppl 1):S99
  38. Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and ...

    Authors: Marian L Hamshere, Ricardo Segurado, Valentina Moskvina, Ivan Nikolov, Beate Glaser and Peter A Holmans
    Citation: BMC Proceedings 2007 1(Suppl 1):S100

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