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Subsequently, all datasets were standardized to zero mean and unit variance to analyze datasets without regard to their scale and location.
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All the datasets were standardized to 30 million tag count so as to be comparable to each other.
Both datasets were standardized using a pipeline explained in our previous work [28].
The datasets were standardized with regard to measurement variable, reference system, spatial coverage and spatial resolution.
The collected microarray datasets were standardized by using quantile normalization.
According to Cordenonsi et al., [ 46] clinical information among the various datasets was standardized redefining the outcome descriptions based on the clinical annotations of each individual study.
The individual gene expression values across the whole dataset were standardized using z-scores to enable the data from different genes to be combined.
The analysis techniques for each dataset are standardized, and the results from each dataset are what is shared.
The entire mouse gene expression dataset was standardized employing principal components of the Affymetrix control probe sets [ 24].
In all datasets, samples were standardized to zero mean and unit variances before other analyses were performed.
All data were standardized using exogenous standards.
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