01-NewmanPaired-class: Class "NewmanPaired"
In NewmanOmics: Extending the Newman Studentized Range Statistic to Transcriptomics

NewmanPaired-class

R Documentation

Class "NewmanPaired"

Description

Represents the reusults of computing the Newman Paired test statistic on one or more paired samples.

Creating Objects

In practice, users will use the pairedStat function to construct an object of the NewmanPaired class. Hand construction is strongly discouraged.

Slots

pairedMean:: A matrix of size N (number of features) by S (number of sample pairs). The mean expression of each feature in each paired sample. Also called "A" in the M-versus-A plots of the microarray era.
difference:: A matrix of size N (number of features) by S (number of sample pairs). The difference (perturbed - base) in expression of each feature in each paired sample. Also called "M" in the M-versus-A plots of the microarray era.
smoothSD:: A matrix of size N (number of features) by S (number of sample pairs). The results of fitting a loess smooth to the relationship between the PairedMean and the observed estimate of standard deviation (i.e., abs(difference)/sqrt(2)).
nuStatistics:: A matrix of size N (number of features) by S (number of sample pairs). The Newman paired statistics, nu.
pValues:: A matrix of size N (number of features) by S (number of sample pairs). Empirical p-values for the Newman statistics.

Methods

x[i,j]: Select a subset of features or sample pairs.
dim(x): The dimension, N by S, of the object.
plot(x, y, which = NULL, ask = NULL, high = 0.99, low = 0.01, ...): Plot the results of the analysis of one sample pair.
hist(x, breaks=101, xlab="P-value", ...): Plot a histogram of the p-values for one sample-pair.

Author(s)

Kevin R. Coombes krc@silicovore.com

References

Abrams ZB, Joglekar A, Gershkowitz GR, Sinicropi-yao S, Asiaee A, Carbone DP, Coombes KR. Personalized Transcriptomics: Selecting Drugs Based on Gene Expression Profiles. Preprint.