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10.1002/gepi.21892 http://scihub22266oqcxt.onion/10.1002/gepi.21892 C4459524!4459524!25740221     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Genet+Epidemiol 2015 ; 39 (4): 227-38 Nephropedia Template TP {{tp|p=25740221|t=2015. Methods for Association Analysis and Meta-Analysis of Rare Variants in Families |pdf=|usr=}}{{25740221}} gab.com Text Methods for Association Analysis and Meta-Analysis of Rare Variants in Families JO: Genet Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=25740221 #FOAvip Advances in exome sequencing and the development of exome genotyping arrays are enabling explorations of association between rare coding variants and complex traits. To ensure power for these rare variant analyses, a variety of association tests that group variants by gene or functional unit have been proposed. Here, we extend these tests to family-based studies. We develop family-based burden tests, variable frequency threshold tests and sequence kernel association tests (SKAT). Through simulations we compare the performance of different tests. We describe situations where family-based studies provide greater power than studies of unrelated individuals to detect rare variants associated with moderate to large changes in trait values. Broadly speaking, we find that when sample sizes are limited and only a modest fraction of all trait-associated variants can be identified, family samples are more powerful. Finally, we illustrate our approach by analyzing the relationship between coding variants and HDL in 11,556 individuals from the HUNT and SardiNIA studies, demonstrating association for coding variants in the APOC3, CETP, LIPC, LIPG, and LPL genes and illustrating the value of family samples, meta-analysis and gene-level tests. Our methods are implemented in freely available C++ code. Twit Text FOAVip Methods for Association Analysis and Meta-Analysis of Rare Variants in Families ????Genet Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=25740221 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25740221 #FOAvip English Wikipedia <ref>{{Cite pmid|25740221}}</ref> Methods for Association Analysis and Meta-Analysis of Rare Variants in Families #MMPMID25740221 Feng S; Pistis G; Zhang H; Zawistowski M; Mulas A; Zoledziewska M; Holmen OL; Busonero F; Sanna S; Hveem K; Willer C; Cucca F; Liu DJ; Abecasis GR Genet Epidemiol 2015[May]; 39 (4): 227-38 PMID25740221show ga Advances in exome sequencing and the development of exome genotyping arrays are enabling explorations of association between rare coding variants and complex traits. To ensure power for these rare variant analyses, a variety of association tests that group variants by gene or functional unit have been proposed. Here, we extend these tests to family-based studies. We develop family-based burden tests, variable frequency threshold tests and sequence kernel association tests (SKAT). Through simulations we compare the performance of different tests. We describe situations where family-based studies provide greater power than studies of unrelated individuals to detect rare variants associated with moderate to large changes in trait values. Broadly speaking, we find that when sample sizes are limited and only a modest fraction of all trait-associated variants can be identified, family samples are more powerful. Finally, we illustrate our approach by analyzing the relationship between coding variants and HDL in 11,556 individuals from the HUNT and SardiNIA studies, demonstrating association for coding variants in the APOC3, CETP, LIPC, LIPG, and LPL genes and illustrating the value of family samples, meta-analysis and gene-level tests. Our methods are implemented in freely available C++ code. äMethods for Association Analysis and Meta-Analysis of Rare Variants in(epmc).pdf DeepDyve Pubget Overpricing