filter.std: Filtering of genes based on their standard deviation.
In Mfuzz: Soft clustering of time series gene expression data

Description Usage Arguments Value Note Author(s) Examples

View source: R/filter.std.R

This function can be used to exclude genes with low standard deviation.

1	filter.std(eset,min.std,visu=TRUE)

`eset`	object of the class ExpressionSet.
`min.std`	threshold for minimum standard deviation. If the standard deviation of a gene's expression is smaller than `min.std` the corresponding gene will be excluded.
`visu`	If `visu` is set to `TRUE`, the ordered standard deviations of genes' expression values will be plotted.

The function produces an object of the ExpressionSet class. It is the same as the input eset object, except for the genes excluded.

As soft clustering is noise robust, pre-filtering can usually be avoided. However, if the number of genes with small expression changes is large, such pre-filtering may be necessary to reduce noise.

Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)

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data(yeast) # data set includes 17 measurements
yeastF <- filter.NA(yeast) # filtering of genes based on missing values 
yeastF <- filter.std(yeastF,min.std=0.3) # filtering of genes based on standard deviation