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10.1093/hmg/ddv260 http://scihub22266oqcxt.onion/10.1093/hmg/ddv260 C4572002!4572002 !26157023     free     free     free Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26157023 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Hum+Mol+Genet 2015 ; 24 (R1 ): R111-9 Nephropedia Template TP {{tp|p=26157023 |t=2015. Strategies for fine-mapping complex traits |pdf=|usr=}}{{26157023 }} gab.com Text Strategies for fine-mapping complex traits JO: Hum Mol Genet http://www.kidney.de/pget.php?&tw=1&pmid=26157023 #FOAvip Genome-wide association studies (GWAS) have identified thousands of robust and replicable genetic associations for complex disease. However, the identification of the causal variants that underlie these associations has been more difficult. This problem of fine-mapping association signals predates GWAS, but the last few years have seen a surge of studies aimed at pinpointing causal variants using both statistical evidence from large association data sets and functional annotations of genetic variants. Combining these two approaches can often determine not only the causal variant but also the target gene. Recent contributions include analyses of custom genotyping arrays, such as the Immunochip, statistical methods to identify credible sets of causal variants and the addition of functional genomic annotations for coding and non-coding variation to help prioritize variants and discern functional consequence and hence the biological basis of disease risk. Twit Text FOAVip Strategies for fine-mapping complex traits ????Hum Mol Genet http://www.kidney.de/pget.php?&tw=1&pmid=26157023 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26157023 #FOAvip English Wikipedia <ref>{{Cite pmid|26157023 }}</ref> Strategies for fine-mapping complex traits #MMPMID26157023 Spain SL ; Barrett JC Hum Mol Genet 2015[Oct]; 24 (R1 ): R111-9 PMID26157023 show ga Genome-wide association studies (GWAS) have identified thousands of robust and replicable genetic associations for complex disease. However, the identification of the causal variants that underlie these associations has been more difficult. This problem of fine-mapping association signals predates GWAS, but the last few years have seen a surge of studies aimed at pinpointing causal variants using both statistical evidence from large association data sets and functional annotations of genetic variants. Combining these two approaches can often determine not only the causal variant but also the target gene. Recent contributions include analyses of custom genotyping arrays, such as the Immunochip, statistical methods to identify credible sets of causal variants and the addition of functional genomic annotations for coding and non-coding variation to help prioritize variants and discern functional consequence and hence the biological basis of disease risk. |*Chromosome Mapping [MESH] |Animals [MESH] |Genetic Variation [MESH] |Genome-Wide Association Study [MESH] |Genotype [MESH] |Humans [MESH]Strategies for fine-mapping complex traits (epmc).pdf DeepDyve Pubget Overpricing