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limma (version 3.28.14)

intraspotCorrelation: Intra-Spot Correlation for Two Color Data

Description

Estimate the within-block correlation associated with spots for spotted two color microarray data.

Usage

intraspotCorrelation(object, design, trim=0.15)

Arguments

object
an MAList object or a list from which M and A values may be extracted
design
a numeric matrix containing the design matrix for linear model in terms of the individual channels. The number of rows should be twice the number of arrays. The number of columns will determine the number of coefficients estimated for each gene.
trim
the fraction of observations to be trimmed from each end of the atanh-correlations when computing the consensus correlation. See mean.

Value

A list with components
consensus.correlation
robust average of the estimated inter-duplicate correlations. The average is the trimmed mean of the correlations for individual genes on the atanh-transformed scale.
atanh.correlations
a numeric vector giving the individual genewise correlations on the atanh scale
df
numeric matrix of degrees of freedom associated with the correlations. The first column gives the degrees of freedom for estimating the within-spot or M-value mean square while the second gives the degrees of freedom for estimating the between spot or A-value mean square.

Details

This function estimates the correlation between two channels observed on each spot. The correlation is estimated by fitting a heteroscedastic regression model to the M and A-values of each gene. The function also returns a consensus correlation, which is a robust average of the individual correlations, which can be used as input for functions lmscFit.

The function may take long time to execute.

References

Smyth, G. K. (2005). Individual channel analysis of two-colour microarray data. Proceedings of the 55th Session of the International Statistics Institute, 5-12 April 2005, Sydney, Australia, Paper 116. http://www.statsci.org/smyth/pubs/ISI2005-116.pdf

See Also

This function uses remlscore from the statmod package.

An overview of methods for single channel analysis in limma is given by 07.SingleChannel.

Examples

Run this code
#  See lmscFit
## Not run: 
# corfit <- intraspotCorrelation(MA, design)
# all.correlations <- tanh(corfit$atanh.correlations)
# boxplot(all.correlations)
# ## End(Not run)

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