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Rather, the relative changes in expression of individual genes between two samples are more informative.
Additional features such as different agglomeration methods for estimating distance between two samples are also added for clustering.
Distinguishing if a given gene expression intensity value is greater than the background noise or is different between two samples are fundamental issues in microarray analysis.
Therefore, abundance differences in single proteins between two samples are much less likely to be masked by other comigrating proteins in 2D-PAGE.
Consequently, for each of these assays, apparent differences in the expression of a gene between two samples are actually differences in expression per unit of RNA or "per transcriptome" (Kanno et al. 2006).
On the other hand, the pairwise distances between two samples are large or even huge mathematically, even if each sample is standardized as a zero-mean point with unit standard deviation.
Similar(54)
Differences between two samples were tested with paired, two-tailed Student's t-tests.
The crucial physical difference between two samples is found from the optical bandgap value.
The two-sided Wilcoxon signed rank test examines the null hypothesis that the median difference between two samples is zero, against the alternative hypothesis that it is not.
Calculating the difference in protein abundance between two samples was a three step process.
The distance between two samples is computed using the Pearson Correlation based distance (5).
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