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Normalisation and statistical analysis of microarray data was performed in R using the Bioconductor packages Limma, Affy and BeadExplorer.
CGHPRO [38] includes both the HMM of Fridlyand [39] and CBS [40], by using the BioConductor packages aCGH and DNAcopy.
Analyses were performed with the Affymetrix CEL files using the Bioconductor packages in the R language and environment as previously described [22].
Both enrichment analyses were performed in R using the Bioconductor packages BioMart [ 39].
Preprocessing and statistical analysis of data was performed using the Bioconductor packages AffylmGUI and Limma ([ 49]).
Data analysis was carried out in-house using the Bioconductor packages snapCGH, DNAcopy and CGHcall.
Similar(36)
Differential gene expression were assessed using linear modeling in R using the bioconductor package Limma that allows for identification of differentially expressed genes in a multifactorial experiment79.
The merged dataset was normalized with RMA [20] using the Bioconductor package, affy.
Microarray data were normalized by the GC-RMA algorithm using the bioconductor package of R software.
Selected KEGG pathways found to be significantly associated with DSS on day 7 were accessed using the bioconductor package KEGGSOAP.
Raw data (.cel files) were imported into R and data were normalized with RMA [20] using the Bioconductor package, affy.
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