clusterSamples | R Documentation |
hclust
function and
various distance metrics derived from percent methylation per base or per
region for each sample.Hierarchical Clustering using methylation data
The function clusters samples using hclust
function and
various distance metrics derived from percent methylation per base or per
region for each sample.
clusterSamples(.Object, dist="correlation", method="ward",
sd.filter=TRUE,sd.threshold=0.5,
filterByQuantile=TRUE, plot=TRUE,chunk.size)
## S4 method for signature 'methylBase'
clusterSamples(
.Object,
dist,
method,
sd.filter,
sd.threshold,
filterByQuantile,
plot
)
## S4 method for signature 'methylBaseDB'
clusterSamples(
.Object,
dist = "correlation",
method = "ward",
sd.filter = TRUE,
sd.threshold = 0.5,
filterByQuantile = TRUE,
plot = TRUE,
chunk.size = 1e+06
)
.Object |
a |
dist |
the distance measure to be used. This must be one of
" |
method |
the agglomeration method to be used. This should be
(an unambiguous abbreviation of) one of " |
sd.filter |
If |
sd.threshold |
A numeric value. If |
filterByQuantile |
A logical determining if |
plot |
a logical value indicating whether to plot hierarchical clustering. (default:TRUE) |
chunk.size |
Number of rows to be taken as a chunk for processing the |
a tree
object of a hierarchical cluster analysis using a set
of dissimilarities for the n objects being clustered.
The parameter chunk.size
is only used when working with
methylBaseDB
objects,
as they are read in chunk by chunk to enable processing large-sized
objects which are stored as flat file database.
Per default the chunk.size is set to 1M rows, which should work for
most systems. If you encounter memory problems or
have a high amount of memory available feel free to adjust the
chunk.size
.
data(methylKit)
clusterSamples(methylBase.obj, dist="correlation", method="ward", plot=TRUE)
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