Sentence examples for background correction and normalisation from inspiring English sources
Both background correction and normalisation were done with RMA (Robust Multichip Average) algorithm (Irizarry et al, 2003).
Background correction and normalisation were performed in the R computing environment (Ihaka and Gentleman, 1996) using the robust multi-array average algorithm.
Single dye labeling of samples, hybridization procedures, data acquisition, background correction and normalisation were performed at the PartnerChip facilities following the standard protocol defined by NimbleGen [ 103, 104].
Background correction and normalisation of the dataset have been performed using the Affy package of Bioconductor (RMA algorithm) in the statistical environment, R (version 2.10.1).
Expression data from 36 OVCA cell lines were subjected to background correction and normalisation using the Robust Multichip Average algorithm in the Affymetrix Expression Console (http://www.affymetrix.com).
The Affymetrix signal extractions showed a much larger heterogeneity than the background corrections and normalisations used on the other platforms.
We used RMA and Bioconductor in R [70] for background correction and normalization [71], [72].
Arrays were normalized using RMA background correction and quantile normalisation in R v.2.15 (Additional file 3).
Background correction and quantile normalisation via the dasen method were conducted individually for the two applied chemistries (Infinium I and II) as well as for the intensities of methylation (m) and un-methylation (u).
Currently Guide can also perform background correction and quantile normalisation [ 18] automatically for Illumina Mouse WG-6 v2.0 array, thus making it more convenient for the user by requiring only the raw data as input.
More details on sample preparation is given in previous descriptions of this experiment [ 29] and the data is available in GEO [ 45] with the accession number GSE53170 [ 46]. Background correction and quantile normalisation was performed on the microarray data (GSE53170) using the R package LIMMA [ 47] from Bioconductor [ 48].
