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limma

arrayWeightsQuick

Array Quality Weights

Description

Estimates relative quality weights for each array in a multi-array experiment with replication.

Usage

arrayWeightsQuick(y, fit)

Arguments

y

the data object used to estimate fit. Can be of any class which can be coerced to matrix, including matrix, MAList, marrayNorm or ExpressionSet.
fit

MArrayLM fitted model object

Details

Estimates the relative reliability of each array by measuring how well the expression values for that array follow the linear model.

This is a quick and dirty version of arrayWeights.

Value

Numeric vector of weights of length ncol(fit).

Author(s)

Gordon Smyth

References

Ritchie, M. E., Diyagama, D., Neilson, van Laar, R., J., Dobrovic, A., Holloway, A., and Smyth, G. K. (2006). Empirical array quality weights in the analysis of microarray data. BMC Bioinformatics 7, 261. http://www.biomedcentral.com/1471-2105/7/261

See Also

See arrayWeights. An overview of LIMMA functions for reading data is given in 03.ReadingData.

Examples

## Not run: 
fit <- lmFit(y, design)
arrayWeightsQuick(y, fit)

## End(Not run)
limma

Linear Models for Microarray Data

v3.46.0
GPL (>=2)
Authors
Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb]
Initial release
2020-10-19

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