clusterCt: Clustering of qPCR Ct values

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/clusterCt.R


Hierarchical clustering of samples or genes from high-throughput qPCR experiments, such as the TaqMan Low Density Array platform. Individual clusters can be selected, and the features within them listed in the given order.


clusterCt(q, main = NULL, type = "genes", dist = "pearson", xlab = "Cluster dendrogram", n.cluster, h.cluster, select.cluster = FALSE, ...)



object of class qPCRset.


character string, plot title.


character string, either "genes" (default) or "samples", indicating what is to be clustered.


character string, specifying whether to use "pearson" correlation (default) or "euclidean" distance for the clustering.


character string, label for the x-axis.


integer, the number of cluster to divide the dendrogram into. See details.


numeric, the height at which to cut the dendrogram into clusters. See details.


logical, whether to select clusters interactively. See details.


any other arguments will be passed to the plot function.


This function may be used to cluster the Ct values and present the result as a dendrogram.

The n.cluster and h.cluster parameters are from the rect.hclust function and can be used to divide the dendrogram into subclusters based on either number of clusters or height of branch, drawing boxes around subclusters. The members of each cluster can be returned (see value). If n.cluster is specified h.cluster will be ignored.

If select.cluster is chosen individual subclusters can be selected and marked by a box by clicking on their highest comment branch with the (first) mouse button. Multiple clusters can be selected until any mouse button other than the first is pressed, and the function can be used in conjunction with either n.cluster or h.cluster. The members of each cluster will likewise be returned, in the order they were selected.


A plot is created on the current graphics device. If any subclusters are marked, these will be returned invisibly in a list, with one component for each subcluster. The individual slots in the list contain the names of the genes, and their position in the original input data (row number).


Heidi Dvinge

See Also

hclust, dist, rect.hclust, identify.hclust


# Load example data
# Clustering samples
clusterCt(qPCRraw, type="samples")
clusterCt(qPCRraw, type="samples", dist="euclidean")
# Clustering genes
clusterCt(qPCRraw, type="genes", cex=0.5)
clusterCt(qPCRraw, type="genes", h.cluster=1.5, cex=0.5)
cluster.list <- clusterCt(qPCRraw, type="genes", n.cluster=6, cex=0.5)

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,, cbind, colMeans, colSums, colnames,,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax,,
    pmin,, 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: RColorBrewer
Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':


Warning message:
In read.dcf(con) :
  URL '': status was 'Couldn't resolve host name'
  Gene4   Gene6  Gene11  Gene16   Gene4  Gene11  Gene13  Gene16  Gene28  Gene30 
      4       6      12      17      28      36      38      41      53      55 
 Gene32  Gene33  Gene35  Gene38  Gene44  Gene28  Gene30  Gene32  Gene33  Gene35 
     57      58      60      63      69      77      79      81      82      84 
 Gene38  Gene44  Gene51  Gene63  Gene51  Gene63  Gene85  Gene90  Gene85  Gene95 
     87      93     100     112     124     136     158     163     181     190 
 Gene96  Gene99 Gene102  Gene96  Gene99 Gene102 Gene110 Gene122 Gene125 Gene126 
    191     194     197     215     218     221     229     241     244     245 
Gene136 Gene143 Gene122 Gene125 Gene126 Gene136 Gene139 Gene143 Gene153 Gene154 
    255     262     265     268     269     279     282     286     296     297 
Gene155 Gene157 Gene159 Gene161 Gene167 Gene153 Gene154 Gene155 Gene157 Gene159 
    298     300     302     304     310     320     321     322     324     326 
Gene161 Gene167 Gene171 Gene181 Gene191 Gene171 Gene181 Gene191 
    328     334     338     348     358     362     372     382 

HTqPCR documentation built on Nov. 1, 2018, 2:23 a.m.