filter.std: Filtering of genes based on their standard deviation.

In Mfuzz: Soft clustering of time series gene expression data

Description

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

Usage

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

Arguments

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.

Value

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

Note

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.

Author(s)

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

Examples

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 

Mfuzz documentation built on May 31, 2017, 10:59 a.m.

Filtering of genes based on number of non-available...

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K-means clustering for gene expression data