virtualArray

[…] (qn) from the r package lumi []. in both cases, genes with low variability expression values were discarded to reduce false-positive rates., data from both platforms were integrated with the virtualarray software r package []. this software allows data from different microarray platforms to be merged by considering several batch effect removal and cross-platform correction methods. […]

[…] a specific comparison demanded two expression arrays from different platforms because the data were not present in the gse to enable comparison of the two tissues, we used the bioconductor package virtualarray, which enables the combination of raw expression data of different microarray platforms regardless of the platform and chip generation method used. the package generates a combined […]

[…] datasets generated in this study were compared with data from previous studies, deposited in public databases (ncbi gene expression omnibus, geo; ) []. r/bioconductor and the software package “virtualarray” were used to combine all data into one dataset (virtual array) [,]. the resulting new array was exported and analyzed in tm4 mev [] and archaeopteryx [], which was further used […]

[…] , . large platform specific batch effects were observed between the two datasets, so an unsupervised empirical bayes method was used to remove these batch effects after as implemented in the ‘virtualarray’ package . the two datasets were merged on common genes after multiple probes that mapped to the same gene were collapsed by taking the median expression value per sample. genes […]

[…] on our human data set and previously described mescs and episcs, and naive and primed hesc gene expression data sets (gse23402, gse15603, gse7866, gse29397, gse43421 and gse43398). we used the virtualarray r/bioconductor package to combine and normalize the different data sets, collapse by median probes targeting the same genes and identify genes present in all data sets, using gene […]