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The Diff Score is a transformation of the p-value that provides directionality to the p-value based on the difference between the average signal in the reference group vs. the comparison group. The formula is: DiffScore = 10*sgn(µcond-µref)*log10p;
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A. Two cutoffs are needed because small number of residues have low p-value, but relatively high entropy. We noticed this a while ago and always wanted to go after these residues as they can be variable (higher entropy) surface residues that are
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R. J. Feise. BMC Med Res Methodol 2002: 2(1); 8. BACKGROUND: Readers may question the interpretation of findings in clinical trials when multiple outcome measures are used without adjustment of the p-value. This question arises because of the
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The t-test value is the t-test statistic derived from the Student's t-test. The larger the absolute value of the t-test statistic, the greater the effect size between the two classes. The p-Value reflects the significance of the differential
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We have tried to give an indication of the biological significance of any r-value by calculating a p-value and an E-value for each result. For an observed correlation ro, the p value was defined as p = P(r >= ro) if ro >= 0, or p= P(r <= ro)
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We searched for statistically overrepresented GO terms associated with target genes with a threshold of the p-
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Pathway-Express provides two types of p-values for each pathway: i) p-value obtained using the classical statistics (referred to as classical p-value) and ii) p-value obtained using the impact analysis (referred to as gamma p-value). This classical
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Summary: The p-value tells you how likely it is to get the sample you got (or a more extreme sample) if the null hypothesis is true. Many people are confused about the p-value and try to read too much into it. In your experiment, you got a certain
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P value adjustment is an essential part of microarray analysis. Raw p values are calculated for each individual gene on a microarray using a t test, for example. But since there are about 40,000 different probes on a typical gene expression array,
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A clusteredness metric is defined as the mean (over genes) of the city-block map distance from a gene to the closest other gene (small values are better). The clusteredness metric is calculated for the genes in question (e.g. with a given GO term).
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