The goals of this project are to develop improved quantitative methods for analysis of genetic data gathered in family and population studies of complex diseases, and to implement these methods in easy to use computer programs. Such methods are required to unravel the complex genetic basis of common diseases. New methods will be developed for the following tasks: Faster and more memory-efficient multi-point analysis of both qualitative and quantitative traits in arbitrarily large and complex pedigrees;Testing haplotypes for association with disease;Multipoint linkage disequilibrium analysis; SNP-based association studies. New technologies are allowing collection of increasingly large amounts of polymorphism data on common disease samples drawn from both families and populations. The new methods developed for this project will enable efficient use of these data, and will improve researchers'ability to detect true genetic effects on disease susceptibility and to distinguish them from statistical noise. The computer programs will be freely distributed to the broader research community to ensure that the methods are widely and readily applied to real-world problems.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Method to Extend Research in Time (MERIT) Award (R37)
Project #
5R37MH059520-13
Application #
7735587
Study Section
Special Emphasis Panel (NSS)
Program Officer
Bender, Patrick
Project Start
1998-12-01
Project End
2011-11-30
Budget Start
2009-12-01
Budget End
2010-11-30
Support Year
13
Fiscal Year
2010
Total Cost
$370,244
Indirect Cost
Name
Princeton University
Department
Type
Organized Research Units
DUNS #
002484665
City
Princeton
State
NJ
Country
United States
Zip Code
08544
Breunig, Jeffrey S; Hackett, Sean R; Rabinowitz, Joshua D et al. (2014) Genetic basis of metabolome variation in yeast. PLoS Genet 10:e1004142
Andersen, Erik C; Bloom, Joshua S; Gerke, Justin P et al. (2014) A variant in the neuropeptide receptor npr-1 is a major determinant of Caenorhabditis elegans growth and physiology. PLoS Genet 10:e1004156
Bloom, Joshua S; Ehrenreich, Ian M; Loo, Wesley T et al. (2013) Finding the sources of missing heritability in a yeast cross. Nature 494:234-7
Khan, Zia; Bloom, Joshua S; Amini, Sasan et al. (2012) Quantitative measurement of allele-specific protein expression in a diploid yeast hybrid by LC-MS. Mol Syst Biol 8:602
Andersen, Erik C; Gerke, Justin P; Shapiro, Joshua A et al. (2012) Chromosome-scale selective sweeps shape Caenorhabditis elegans genomic diversity. Nat Genet 44:285-90
Ghosh, Rajarshi; Andersen, Erik C; Shapiro, Joshua A et al. (2012) Natural variation in a chloride channel subunit confers avermectin resistance in C. elegans. Science 335:574-8
Ehrenreich, Ian M; Bloom, Joshua; Torabi, Noorossadat et al. (2012) Genetic architecture of highly complex chemical resistance traits across four yeast strains. PLoS Genet 8:e1002570
Torabi, Noorossadat; Kruglyak, Leonid (2012) Genetic basis of hidden phenotypic variation revealed by increased translational readthrough in yeast. PLoS Genet 8:e1002546
Ghosh, Rajarshi; Mohammadi, Aylia; Kruglyak, Leonid et al. (2012) Multiparameter behavioral profiling reveals distinct thermal response regimes in Caenorhabditis elegans. BMC Biol 10:85
Foss, Eric J; Radulovic, Dragan; Shaffer, Scott A et al. (2011) Genetic variation shapes protein networks mainly through non-transcriptional mechanisms. PLoS Biol 9:e1001144

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