M. Rattray, Jing Yang, Sumon Ahmed, A. Boukouvalas
{"title":"Modelling Gene Expression Dynamics with Gaussian Process Inference","authors":"M. Rattray, Jing Yang, Sumon Ahmed, A. Boukouvalas","doi":"10.1002/9781119487845.ch31","DOIUrl":"https://doi.org/10.1002/9781119487845.ch31","url":null,"abstract":"","PeriodicalId":216924,"journal":{"name":"Handbook of Statistical Genomics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121106128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evolutionary Quantitative Genetics","authors":"B. Walsh","doi":"10.1002/0470022620.BBC15","DOIUrl":"https://doi.org/10.1002/0470022620.BBC15","url":null,"abstract":"Evolutionary quantitative genetics is the study of how complex traits evolve over time. While this field builds on traditional concepts from quantitative genetics widely used by applied breeders and human geneticists (in particular, the inheritance of complex traits), its unique feature is in examining the role of natural selection in changing the population distribution of a complex trait over time. Our review focuses on this role of selection, starting with response under the standard infinitesimal model, in which trait variation is determined by a very large number of loci, each of small effect. We then turn to issues of measuring fitness (and hence natural selection) on both univariate and multivariate traits. We conclude by examining models that treat fitness itself as a complex trait.","PeriodicalId":216924,"journal":{"name":"Handbook of Statistical Genomics","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127508594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Genome‐Wide Association Studies","authors":"A. Morris, L. Cardon","doi":"10.1002/9781119487845.ch21","DOIUrl":"https://doi.org/10.1002/9781119487845.ch21","url":null,"abstract":"","PeriodicalId":216924,"journal":{"name":"Handbook of Statistical Genomics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132173826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Conservation Genetics","authors":"M. A. Beaumont","doi":"10.1002/9780470061619.ch30","DOIUrl":"https://doi.org/10.1002/9780470061619.ch30","url":null,"abstract":"","PeriodicalId":216924,"journal":{"name":"Handbook of Statistical Genomics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131022389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive Molecular Evolution","authors":"Ziheng Yang","doi":"10.1002/0470022620.BBC10","DOIUrl":"https://doi.org/10.1002/0470022620.BBC10","url":null,"abstract":"This chapter reviews statistical methods for detecting adaptive molecular evolution by comparing synonymous and nonsynonymous substitution rates in protein-coding DNA sequences. A Markov process model of codon substitution, which forms the basis for all later discussions in this chapter, is introduced first. The case of comparing two sequences to estimate the numbers of synonymous (dS) and nonsynonymous (dN ) substitutions per site is then considered. The maximum likelihood (ML) method and a number of ad hoc counting methods are evaluated. The rest of the chapter deals with joint analyses of multiple sequences on a phylogeny. Review is done on Markov models of codon substitution that allow the nonsynonymous/synonymous rate ratio (ω = dN /dS) to vary among branches in a phylogeny or among amino acid sites in a protein. Those models can be used to construct likelihood ratio tests (LRTs) to identify evolutionary lineages under episodic Darwinian selection or to infer critical amino acids in a protein under diversifying selection. Real-data examples are used to demonstrate the application of the methods. The chapter finishes with a discussion of the limitations of current methods.","PeriodicalId":216924,"journal":{"name":"Handbook of Statistical Genomics","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128380599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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