caa a22 4500 378925911 CHVBK 20180305123617.0 cr unu---uuuuu 161128e20041031xx s 000 0 eng 10.2202/1544-6115.1046 doi (NATIONALLICENCE)gruyter-10.2202/1544-6115.1046 MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data [Elektronische Daten] [Leslie Cope, Xiaogang Zhong, Elizabeth Garrett, Giovanni Parmigiani] Cross-study validation of gene expression investigations is critical in genomic analysis. We developed an R package and associated object definitions to merge and visualize multiple gene expression datasets. Our merging functions use arbitrary character IDs and generate objects that can efficiently support a variety of joint analyses. Visualization tools support exploration and cross-study validation of the data, without requiring normalization across platforms. Tools include "integrative correlation" plots that is, scatterplots of all pairwise correlations in one study against the corresponding pairwise correlations of another, both for individual genes and all genes combined. Gene-specific plots can be used to identify genes whose changes are reliably measured across studies. Visualizations also include scatterplots of gene-specific statistics quantifying relationships between expression and phenotypes of interest, using linear, logistic and Cox regression. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston Computational Biology/Bioinformatics nationallicence Microarrays nationallicence gene expression micorarrays nationallicence R nationallicence validation nationallicence meta-analysis nationallicence Cope Leslie The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins aut Zhong Xiaogang Department of Applied Mathematics and Statistics, Johns Hopkins University aut Garrett Elizabeth The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins aut Parmigiani Giovanni The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins aut Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-10-31), 1-13 3:1<1 2004 3 sagmb https://doi.org/10.2202/1544-6115.1046 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1544-6115.1046 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cope Leslie The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins aut NATIONALLICENCE 700 1- Zhong Xiaogang Department of Applied Mathematics and Statistics, Johns Hopkins University aut NATIONALLICENCE 700 1- Garrett Elizabeth The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins aut NATIONALLICENCE 700 1- Parmigiani Giovanni The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins aut NATIONALLICENCE 773 0- Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-10-31), 1-13 3:1<1 2004 3 sagmb CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter