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The results were highly significant when analyzed by comparing different quality control measures: raw Q, background (bkg), scaling factor (SF), percent present calls (%P), chips pseudo-images, normalized unscaled standard errors (NUSE) and relative log expression (RLE).
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The difference in the Kaplan-Meier survival curves was highly statistically significant when analyzed by the log-rank statistic for the KRAS-wildtype group.
The difference was statistically significant when analyzed by categorical analysis (Table 2).
In this instance, it is unclear whether the problem with rs12315364 would have been automatically detected becaus it is not, in fact, significant when analyzed in PLINK using single-SNP logistic regression (with 3 principal components included as covariates), although it is highly (and suspiciously) significant when analyzed instead using the Armitage trend test.
This difference was also significant when analyzing MSS tumors only, (P = 0.03).
The interaction was significant when analyzing all groups together.
Correlations between LIDAR data and aboveground tree biomass measured in the field were highly significant when all three 1 km2 areas were analyzed collectively, with the 80th percentile again explaining the greatest amount of variability (74%).
This is highly significant when designing molecular switches to perform logic operations.
The mathematical model was highly significant when compared to a null model (p < 0.0001).
were highly significant when compared with the substrate pre-miR-151, in both cases P < 0.002.
Differences were considered significant when p<0.01, and highly significant when p<0.0001.
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CEO of Professional Science Editing for Scientists @ prosciediting.com