Luis León-Novelo, Kaisa M Kemppainen, Alexandria Ardissone, Austin Davis-Richardson, Jennie Fagen, Kelsey Gano, Eric W Triplett
{"title":"TWO APPLICATIONS OF PERMUTATION TESTS IN BIOSTASTICS.","authors":"Luis León-Novelo, Kaisa M Kemppainen, Alexandria Ardissone, Austin Davis-Richardson, Jennie Fagen, Kelsey Gano, Eric W Triplett","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>We show two examples of how we answer biological questions by converting them into statistical hypothesis testing problems. We consider gene abundance data, and apply permutation tests. Though these tests are simple, they allow us to test biologically relevant hypotheses. Here we present the analysis of data rising from two studies on Type 1 Diabetes. In the first study [3] are interested in comparing the gut bacterial biodiversity in children at risk and not at risk of developing diabetes. In the second study, [4] compare the gut bacterial biodiversity of children in six different sites in USA and Europe. The statistical analyses presented here are parts of the \"statistical methods\" in two papers mentioned above. Here we offer a detailed explanation of the \"Statistical Methods\" addressed to readers with a statistics background.</p>","PeriodicalId":93912,"journal":{"name":"Boletin de la Sociedad Matematica Mexicana","volume":"19 2","pages":"255-266"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159102/pdf/nihms-608319.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Boletin de la Sociedad Matematica Mexicana","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We show two examples of how we answer biological questions by converting them into statistical hypothesis testing problems. We consider gene abundance data, and apply permutation tests. Though these tests are simple, they allow us to test biologically relevant hypotheses. Here we present the analysis of data rising from two studies on Type 1 Diabetes. In the first study [3] are interested in comparing the gut bacterial biodiversity in children at risk and not at risk of developing diabetes. In the second study, [4] compare the gut bacterial biodiversity of children in six different sites in USA and Europe. The statistical analyses presented here are parts of the "statistical methods" in two papers mentioned above. Here we offer a detailed explanation of the "Statistical Methods" addressed to readers with a statistics background.