Sentence examples for differential expression analyzed from inspiring English sources
Transcript reads were normalized and differential expression analyzed with DESeq2 (Love et al. 2014).
Read counts for each of the nine samples were extracted and used for differential expression analyzes using the EdgeR package in Bioconductor 3.0 (Robinson et al. 2009).
Differential gene expression, analyzed with Illumina Beadstation, was used to detect intracellular signaling resulting in changed transcription, compared to control cells (n = 2 in each group).
Significant changes in gene expression were calculated using R statistics (R value ≥ 9) (Additional file 14) and resulted in 2,026 genes, which seemed to be differentially regulated, and their differential expression was analyzed using Pearson uncentered correlation [ 18].
Differential expression was analyzed using publically available data sets from the gene expression omnibus (GEO) and ImmuSort databases (Wang et al.,2015).
Differential expression was analyzed using the limma package [ 33].
Differential expression was analyzed using DESeq Version 1.16.0 (Anders and Huber, 2010).
Predicted target genes for miRNAs, including members of the miR156 family whose family members showed highly differential expression, were analyzed.
Reads were mapped using TopHat v1.4.1 and differential expression was analyzed using Cuffdiff v2.1.1 (Trapnell et al. 2012).
Differential expression is analyzed using functions from the Bioconductor limma package [ 16] and significant differential expression is assigned on the basis of the multiplicity of the tests.
Differential expression was analyzed using SageBetaBin (31), and expression values [reads per kilobase of transcript per million reads read (RPKM ] were calculated according to Mortazavi et al. (32).
