Detecting gene|[ndash]|gene interactions that underlie human diseases Export

@article{citeulike:4527514, abstract = {Following the identification of several disease-associated polymorphisms by genome-wide association (GWA) analysis, interest is now focusing on the detection of effects that, owing to their interaction with other genetic or environmental factors, might not be identified by using standard single-locus tests. In addition to increasing the power to detect associations, it is hoped that detecting interactions between loci will allow us to elucidate the biological and biochemical pathways that underpin disease. Here I provide a critical survey of the methods and related software packages currently used to detect the interactions between genetic loci that contribute to human genetic disease. I also discuss the difficulties in determining the biological relevance of statistical interactions.}, author = {Cordell, Heather J.}, citeulike-article-id = {4527514}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nrg2579}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nrg2579}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/19434077}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=19434077}, day = {01}, doi = {10.1038/nrg2579}, issn = {1471-0056}, journal = {Nature Reviews Genetics}, keywords = {carrie, gwas, methods, review, rotation}, month = {June}, number = {6}, pages = {392--404}, posted-at = {2009-05-27 20:41:44}, priority = {2}, publisher = {Nature Publishing Group}, title = {Detecting gene|[ndash]|gene interactions that underlie human diseases}, url = {http://dx.doi.org/10.1038/nrg2579}, volume = {10}, year = {2009} }

TY - JOUR ID - citeulike:4527514 L3 - citeulike-article-id:4527514 N2 - Following the identification of several disease-associated polymorphisms by genome-wide association (GWA) analysis, interest is now focusing on the detection of effects that, owing to their interaction with other genetic or environmental factors, might not be identified by using standard single-locus tests. In addition to increasing the power to detect associations, it is hoped that detecting interactions between loci will allow us to elucidate the biological and biochemical pathways that underpin disease. Here I provide a critical survey of the methods and related software packages currently used to detect the interactions between genetic loci that contribute to human genetic disease. I also discuss the difficulties in determining the biological relevance of statistical interactions. IS - 6 JF - Nature Reviews Genetics SN - 1471-0056 EP - 404 TI - Detecting gene|[ndash]|gene interactions that underlie human diseases PB - Nature Publishing Group VL - 10 SP - 392 KW - carrie KW - gwas KW - methods KW - review KW - rotation AU - Cordell, Heather PY - 2009/06/01/ UR - http://dx.doi.org/10.1038/nrg2579 ER -