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The partial improvement of survival prediction and risk association that were observed for OS endpoint were also obtained with respect to RFS. Between the merged data sets, Z-score normalization provided higher results than ComBat even though the difference is not significant (see supplementary information file, Table S3 to S6).
The bold font denotes the enriched miRNA target gene sets (z-score > 2.0).
A looser cutoff was used to select enriched miRNA target gene sets (z-score > 2.0).
To identify such biological drivers, the gene membership of the top 25 best-predicted gene sets (Z-score ≥ 1.9) was reviewed to identify genes that were consistently present.
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The threshold for the site search was defined as the lowest score observed in the training set (Z-score = 4.8).
The so-called gene set Z-score (GSZ) merges both options provided by the gene set overrepresentation and the gene set overexpression approaches [ 10].
Those binding sites having a frequency greater then a set Z-score (average + 2 standard deviations) were considered over-represented and therefore significant based on our own analysis of frequency effects within the genome as well as previous work in eukaryotic species showing a correlation between increased frequency of a binding site and a change in expression [ 56].
The discriminative ability of PCA using gene set Z-scores (as opposed to individual gene values) is illustrated using the individual samples of day 10 versus day 40 fly heads in Figure 8.
For small data sets, the Z-score technique provides a method for determining genes that have significantly different expression in a single sample relative to other samples.
Data were analyzed through the use of causal analysis approaches in IPA to infer upstream biological causes and probable downstream biological effects, using enrichment score (Fisher's Exact Test p-value) to measure overlap between observed and predicted gene sets, and z-score to match observed and predicted up/down regulation patterns [ 40].
To apply our qRT-PCR reduced gene score to these microarray data sets, the expression values of each set were z-score transformed [ 23].
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