Multiple-laboratory comparison of microarray platforms. Export

@article{citeulike:166875, abstract = {Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC-Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well.}, author = {Irizarry, Rafael A. and Warren, Daniel and Spencer, Forrest and Kim, Irene F. and Biswal, Shyam and Frank, Bryan C. and Gabrielson, Edward and Garcia, Joe G. and Geoghegan, Joel and Germino, Gregory and Griffin, Constance and Hilmer, Sara C. and Hoffman, Eric and Jedlicka, Anne E. and Kawasaki, Ernest and Mart\'{\i}nez-Murillo, Francisco and Morsberger, Laura and Lee, Hannah and Petersen, David and Quackenbush, John and Scott, Alan and Wilson, Michael and Yang, Yanqin and Ye, Shui Qing Q. and Yu, Wayne}, citeulike-article-id = {166875}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nmeth756}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nmeth756}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/15846361}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=15846361}, day = {21}, doi = {10.1038/nmeth756}, issn = {1548-7091}, journal = {Nature methods}, keywords = {microarrays}, month = {May}, number = {5}, pages = {345--350}, posted-at = {2008-05-06 00:17:47}, priority = {2}, publisher = {Nature Publishing Group}, title = {Multiple-laboratory comparison of microarray platforms.}, url = {http://dx.doi.org/10.1038/nmeth756}, volume = {2}, year = {2005} }

TY - JOUR ID - citeulike:166875 L3 - citeulike-article-id:166875 N2 - Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC-Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well. IS - 5 JF - Nature methods SN - 1548-7091 EP - 350 TI - Multiple-laboratory comparison of microarray platforms. PB - Nature Publishing Group VL - 2 SP - 345 KW - microarrays AU - Irizarry, Rafael AU - Warren, Daniel AU - Spencer, Forrest AU - Kim, Irene AU - Biswal, Shyam AU - Frank, Bryan AU - Gabrielson, Edward AU - Garcia, Joe AU - Geoghegan, Joel AU - Germino, Gregory AU - Griffin, Constance AU - Hilmer, Sara AU - Hoffman, Eric AU - Jedlicka, Anne AU - Kawasaki, Ernest AU - Martínez-Murillo, Francisco AU - Morsberger, Laura AU - Lee, Hannah AU - Petersen, David AU - Quackenbush, John AU - Scott, Alan AU - Wilson, Michael AU - Yang, Yanqin AU - Ye, Shui Qing AU - Yu, Wayne PY - 2005/05/21/ UR - http://dx.doi.org/10.1038/nmeth756 ER -