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The threshold for the number of microarrays was set by the binomial trial estimate (see Methods).
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Initially, a microarray platform was set up using an unrelated in-house antigen, PUUV recombinant nucleocapsid protein, to optimize the protocol for the detection of antibodies.
The microarray experiment was set up as a reference design, using a RNA pool of all individuals in each generation as reference.
The average of the lowest 2% of probe intensities occurring in each of 16 microarray sectors was set as background and subtracted from all features in that sector.
A linear model in the Bioconductor package LIMMA (Linear models for microarray data) was set up to estimate the M-value and variance for each gene.
We chose a 6 kb cutoff because the Lowess smoothing window size of our microarray data was set at 6 kb.
The experimental design of the microarray study was set up as a time-course factorial design, to best observe the TNFα-induced gene expression changes over time [ 45].
Thresholding for microarray cases were set at <100 Kb for both deletions and duplications as part of routine diagnostic testing criteria.
Promising advances in novel techniques such as tissue microarrays and CGH are set to revolutionise breast cancer diagnosis and prediction.
The oligonucleotide microarray was used to screen two sets of Salmonella strains for the presence of several antibiotic resistance genes.
All microarrays were computed probe sets that summarized each of the eight species using Affymetrix Power Tools [ 26].
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