SeqSIMLA

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Title SeqSIMLA
Short Description SeqSIMLA can simulate sequence data with user-specified disease and quantitative trait models. Family or unrelated case-control data can be simulated.
Long Description SeqSIMLA can simulate sequence data in families with multiple affected and unaffected siblings or unrelated case-control data under different disease models. SeqSIMLA accepts a population of sequences generated by other sequence generators. We implemented two disease models, in which the user can flexibly specify the number of disease loci, effect sizes or population attributable risk, disease prevalence, and risk or protective loci. We also implemented a quantitative trait model, in which the user can specify the number of quantitative trait loci (QTL), proportions of variance explained by the QTL, and genetic models. In 2014, we extended SeqSIMLA to create SeqSIMLA2, which can simulate correlated traits and considers the shared environmental effects. SeqSIMLA2 can also simulate prespecified large pedigree structures. There are no restrictions on the number of individuals that can be simulated in a pedigree. In 2015, we implemented SeqSIMLA2_exact, which can simulate sequences with multiple disease sites in large pedigrees with given disease status for each pedigree member, assuming that the disease prevalence is low.
Version 1.1
Project Started 2013
Last Release 3 years, 2 months ago
Homepagehttp://seqsimla.sourceforge.net/
Citations
  • Chung RH, Tsai WY, Hsieh CH, Hung KY, Hsiung CA, Hauser ER, SeqSIMLA2: simulating correlated quantitative traits accounting for shared environmental effects in user-specified pedigree structure., Genet Epidemiol, Jan. 1, 2015
  • Chung RH, Tsai WY, Hsieh CH, Hung KY, Hsiung CA, Hauser ER, SeqSIMLA2: simulating correlated quantitative traits accounting for shared environmental effects in user-specified pedigree structure., Genet Epidemiol, Jan. 1, 2015 [Abstract, cited in PMC ]
  • Chung RH, Shih CC, SeqSIMLA: a sequence and phenotype simulation tool for complex disease studies., BMC Bioinformatics, June 20, 2013 [Abstract, cited in PMC ]
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