cselection: Repeated soft clustering for detection of empty clusters for...

In Mfuzz: Soft clustering of time series gene expression data

Description

This function performs repeated soft clustering for a range of cluster numbers c and reports the number of empty clusters detected.

Usage

cselection(eset,m,crange=seq(4,32,4),repeats=5,visu=TRUE,...)

Arguments

eset	object of class ExpressionSet.
m	value of fuzzy c-means parameter m.
crange	range of number of clusters c.
repeats	number of repeated clusterings.
visu	If visu=TRUE plot of number of empty clusters is produced.
...	additional arguments for underlying mfuzz.

Details

A soft cluster is considered as empty, if none of the genes has a corresponding membership value larger than 0.5

Value

A matrix with the number of empty clusters detected is generated.

Note

The cselection function may help to determine an accurate cluster number. However, it should be used with care, as the determination remains difficult especially for short time series and overlapping clusters. A better way is likely to perform clustering with a range of cluster numbers and subsequently assess their biological relevance e.g. by GO analyses.

Author(s)

Matthias E. Futschik (http://www.cbme.ualg.pt/mfutschik_cbme.html)

References

M.E. Futschik and B. Charlisle, Noise robust clustering of gene expression time-course data, Journal of Bioinformatics and Computational Biology, 3 (4), 965-988, 2005

L. Kumar and M. Futschik, Mfuzz: a software package for soft clustering of microarray data, Bioinformation, 2(1) 5-7,2007

Examples

if (interactive()){
data(yeast)
# Data pre-processing
yeastF <- filter.NA(yeast)
yeastF <- fill.NA(yeastF)
yeastF <- standardise(yeastF)

#### parameter selection
# Empty clusters should not appear
cl <- mfuzz(yeastF,c=20,m=1.25)
mfuzz.plot(yeastF,cl=cl,mfrow=c(4,5))

# Note: The following calculation might take some time

 tmp  <- cselection(yeastF,m=1.25,crange=seq(5,40,5),repeats=5,visu=TRUE)
 # derivation of number of non-empty clusters (crosses) from diagnonal
 # line  indicate appearance of empty clusters 

# Empty clusters might appear 
cl <- mfuzz(yeastF,c=40,m=1.25)
mfuzz.plot(yeastF,cl=cl,mfrow=c(4,5)) 
 }

Example output

Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: e1071
Warning message:
no DISPLAY variable so Tk is not available 

Mfuzz documentation built on Nov. 8, 2020, 5:22 p.m.