plotDensities {limma} | R Documentation |
Plots the densities of individual-channel intensities for two-color microarray data.
plotDensities(object, log=TRUE, arrays=NULL, singlechannels=NULL, groups=NULL, col=NULL)
object |
an |
log |
logical, should densities be formed and plotted for the log-intensities ( |
arrays |
vector of integers giving the arrays from which the
individual-channels will be selected to be plotted.
Corresponds to columns of |
singlechannels |
vector of integers indicating which
individual-channels will be selected to be plotted. Values correspond
to the columns of the matrix of |
groups |
vector of consecutive integers beginning at 1 indicating
the groups of arrays or individual-channels (depending on which of
|
col |
vector of colors of the same length as the number of
different groups. If |
This function is used as a data display technique associated with between-array normalization, especially individual-channel normalization methods such as quantile-normalization. See the section on between-array normalization in the LIMMA User's Guide.
If no col
is specified, the default is to color individual channels
according to red and green. If both arrays
and groups
are
non-NULL
, then the length of groups
must equal the length
of arrays
and the maximum of groups
(i.e. the number of
groups) must equal the length of col
otherwise the default color
of black will be used for all individual-channels.
If arrays
is NULL
and both singlechannels
and
groups
are non-NULL
, then the length of groups
must
equal the length of singlechannels
and the maximum of groups
(i.e. the number of groups) must equal the length of col
otherwise the default color of black will be used for all individual-channels.
A plot is created on the current graphics device.
Natalie Thorne
An overview of diagnostic plots in LIMMA is given in 09.Diagnostics.
There is a section using plotDensities
in conjunction with between-array normalization
in the LIMMA User's Guide.
## Not run: # This example is designed for work on a subset of the data # from the ApoAI case study in Limma User's Guide # This example was formerly loaded from sma package using # library(sma) # data(MouseArray) # no normalization but background correction is done MA.n <- MA.RG(mouse.data) # Default settings for plotDensities. plotDensities(MA.n) # One can reproduce the default settings. plotDensities(MA.n,arrays=c(1:6),groups=c(rep(1,6),rep(2,6)), col=c("red","green")) # Color R and G individual-channels by blue and purple. plotDensities(MA.n,arrays=NULL,groups=NULL,col=c("blue","purple")) # Indexing individual-channels using singlechannels (arrays=NULL). plotDensities(MA.n,singlechannels=c(1,2,7)) # Change the default colors from c("red","green") to c("pink","purple") plotDensities(MA.n,singlechannels=c(1,2,7),col=c("pink","purple")) # Specified too many colors since groups=NULL defaults to two groups. plotDensities(MA.n,singlechannels=c(1,2,7),col=c("pink","purple","blue")) # Three individual-channels, three groups, three colors. plotDensities(MA.n,singlechannels=c(1,2,7),groups=c(1,2,3), col=c("pink","purple","blue")) # Three individual-channels, one group, one color. plotDensities(MA.n,singlechannels=c(1,2,7),groups=c(1,1,1), col=c("purple")) # All individual-channels, three groups (ctl,tmt,reference), three colors. plotDensities(MA.n,singlechannels=c(1:12), groups=c(rep(1,3),rep(2,3),rep(3,6)),col=c("darkred","red","green")) ## End(Not run)