{"extern":1,"date_published":"2011-01-01T00:00:00Z","intvolume":" 2","acknowledgement":"Anna-Sapfo Malaspinas is supported by a Janggen-Poehn Fellowship. Caroline Uhler is supported by an International Fulbright Science and Technology Fellowship.","year":"2011","quality_controlled":0,"volume":2,"type":"journal_article","_id":"2961","publist_id":"3764","citation":{"apa":"Malaspinas, A., & Uhler, C. (2011). Detecting epistasis via Markov bases. Journal of Algebraic Statistics. Public Knowledge Project. http://dx.doi.org/10.18409/jas.v2i1.27","chicago":"Malaspinas, Anna, and Caroline Uhler. “Detecting Epistasis via Markov Bases.” Journal of Algebraic Statistics. Public Knowledge Project, 2011. http://dx.doi.org/10.18409/jas.v2i1.27.","ama":"Malaspinas A, Uhler C. Detecting epistasis via Markov bases. Journal of Algebraic Statistics. 2011;2(1):36-53. doi:http://dx.doi.org/10.18409/jas.v2i1.27","ista":"Malaspinas A, Uhler C. 2011. Detecting epistasis via Markov bases. Journal of Algebraic Statistics. 2(1), 36–53.","ieee":"A. Malaspinas and C. Uhler, “Detecting epistasis via Markov bases,” Journal of Algebraic Statistics, vol. 2, no. 1. Public Knowledge Project, pp. 36–53, 2011.","short":"A. Malaspinas, C. Uhler, Journal of Algebraic Statistics 2 (2011) 36–53.","mla":"Malaspinas, Anna, and Caroline Uhler. “Detecting Epistasis via Markov Bases.” Journal of Algebraic Statistics, vol. 2, no. 1, Public Knowledge Project, 2011, pp. 36–53, doi:http://dx.doi.org/10.18409/jas.v2i1.27."},"abstract":[{"text":"Rapid research progress in genotyping techniques have allowed large genome-wide association studies. Existing methods often focus on determining associations between single loci and a specic phenotype. However, a particular phenotype is usually the result of complex relationships between multiple loci and the environment. In this paper, we describe a two-stage method for detecting epistasis by combining the traditionally used single-locus search with a search for multiway interactions. Our method is based on an extended version of Fisher's exact test. To\nperform this test, a Markov chain is constructed on the space of multidimensional contingency tables using the elements of a Markov basis as moves. We test our method on simulated data and compare it to a two-stage logistic regression method and to a fully Bayesian method, showing that we are able to detect the interacting loci when other methods fail to do so. Finally, we apply our method to a genome-wide data set consisting of 685 dogs and identify epistasis associated with canine hair length for four pairs of single nucleotide polymorphisms (SNPs).","lang":"eng"}],"author":[{"first_name":"Anna","last_name":"Malaspinas","full_name":"Malaspinas, Anna-Sapfo "},{"orcid":"0000-0002-7008-0216","id":"49ADD78E-F248-11E8-B48F-1D18A9856A87","first_name":"Caroline","last_name":"Uhler","full_name":"Caroline Uhler"}],"oa":1,"date_created":"2018-12-11T12:00:34Z","issue":"1","page":"36 - 53","status":"public","doi":"http://dx.doi.org/10.18409/jas.v2i1.27","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1006.4929"}],"publication_status":"published","day":"01","publication":"Journal of Algebraic Statistics","month":"01","date_updated":"2021-01-12T07:40:05Z","title":"Detecting epistasis via Markov bases","publisher":"Public Knowledge Project"}