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10.1534/genetics.115.183624 http://scihub22266oqcxt.onion/10.1534/genetics.115.183624 C4905536!4905536!26837753     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26837753&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26837753.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Genetics 2016 ; 202 (4): 1563-74 Nephropedia Template TP {{tp|p=26837753|t=2016. The Dissection of Expression Quantitative Trait Locus Hotspots |pdf=|usr=}}{{26837753}} gab.com Text The Dissection of Expression Quantitative Trait Locus Hotspots JO: Genetics http://www.kidney.de/pget.php?&tw=1&pmid=26837753 #FOAvip Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effects on gene expression: expression quantitative trait locus hotspots. We describe a set of exploratory graphical methods as well as a formal likelihood-based test for assessing whether a given hotspot is due to one or multiple polymorphisms. We first look at the pattern of effects of the locus on the expression traits that map to the locus: the direction of the effects and the degree of dominance. A second technique is to focus on the individuals that exhibit no recombination event in the region, apply dimensionality reduction (e.g., with linear discriminant analysis), and compare the phenotype distribution in the nonrecombinant individuals to that in the recombinant individuals: if the recombinant individuals display a different expression pattern than the nonrecombinant individuals, this indicates the presence of multiple causal polymorphisms. In the formal likelihood-based test, we compare a two-locus model, with each expression trait affected by one or the other locus, to a single-locus model. We apply our methods to a large mouse intercross with gene expression microarray data on six tissues. Twit Text FOAVip The Dissection of Expression Quantitative Trait Locus Hotspots ????Genetics http://www.kidney.de/pget.php?&tw=1&pmid=26837753 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26837753 #FOAvip English Wikipedia <ref>{{Cite pmid|26837753}}</ref> The Dissection of Expression Quantitative Trait Locus Hotspots #MMPMID26837753 Tian J; Keller MP; Broman AT; Kendziorski C; Yandell BS; Attie AD; Broman KW Genetics 2016[Apr]; 202 (4): 1563-74 PMID26837753show ga Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effects on gene expression: expression quantitative trait locus hotspots. We describe a set of exploratory graphical methods as well as a formal likelihood-based test for assessing whether a given hotspot is due to one or multiple polymorphisms. We first look at the pattern of effects of the locus on the expression traits that map to the locus: the direction of the effects and the degree of dominance. A second technique is to focus on the individuals that exhibit no recombination event in the region, apply dimensionality reduction (e.g., with linear discriminant analysis), and compare the phenotype distribution in the nonrecombinant individuals to that in the recombinant individuals: if the recombinant individuals display a different expression pattern than the nonrecombinant individuals, this indicates the presence of multiple causal polymorphisms. In the formal likelihood-based test, we compare a two-locus model, with each expression trait affected by one or the other locus, to a single-locus model. We apply our methods to a large mouse intercross with gene expression microarray data on six tissues. äThe Dissection of Expression Quantitative Trait Locus Hotspots (epmc).pdf DeepDyve Pubget Overpricing