Sentence examples for median array and from inspiring English sources

Overall signal strength from arrays was normalized to the median array, and expression levels determined using the perfect match/mismatch (PM/MM) algorithm.

For the disruptant dataset log2 ratios against a virtual median array were calculated and these ratios were then z-transformed within each microarray prior to network inference.

Thousand fifty-three Affymetrix U133A CEL files from various publicly available microarray datasets (GSE17705 [MDACC298] [ 15], GSE6532 [LOI327] [ 16, 17], GSE12093 [ZHANG18]] [ 18], GSE1456 [PAWITAN19]] [ 19] and MDACC133 [ 20]) were processed using MAS 5.0 (R/Bioconductor) to generate probe-level intensities with a median array intensity of 600, and each expression value was log2 transformed.

Samples were compared using the ΔΔCT method by normalizing to SnoRNA202 expression and the median array.

We tried four filtering thresholds: 0, the median array intensity, the third quartile, and one standard deviation above the mean.

Gene expression patterns for each gene were normalized to the median array intensity for all chips and data from infected animals was normalized to uninfected PBS controls [ 18].

Intensities were normalized using average factors scaled to the median array intensities over the entire array by using the median array as a reference.

All features with an intensity less than the median array background intensity (300) were removed from the analysis.

A median array was selected as the reference array for normalization.

For quantile normalization we used the median array as the reference array.

Median array intensities for the three experiments were scaled to the same value prior to normalization in order to provide comparable probe intensities for inter-experimental comparison.