The tooltip shows the median, variance, maximum, minimum and number of non-NA samples of each data series, as well as sample names if available.
Arguments
- data
Numeric, data frame or matrix: gene expression data or alternative splicing event quantification values (sample names are based on their
names
orcolnames
)- groups
List of sample names or vector containing the group name per
data
value (read Details); ifNULL
or a character vector of length 1,data
values are considered from the same group- rug
Boolean: show rug plot?
- vLine
Boolean: plot vertical lines (including descriptive statistics for each group)?
- ...
Arguments passed on to
stats::density.default
bw
the smoothing bandwidth to be used. The kernels are scaled such that this is the standard deviation of the smoothing kernel. (Note this differs from the reference books cited below, and from S-PLUS.)
bw
can also be a character string giving a rule to choose the bandwidth. Seebw.nrd
.
The default,"nrd0"
, has remained the default for historical and compatibility reasons, rather than as a general recommendation, where e.g.,"SJ"
would rather fit, see also Venables and Ripley (2002).The specified (or computed) value of
bw
is multiplied byadjust
.adjust
the bandwidth used is actually
adjust*bw
. This makes it easy to specify values like ‘half the default’ bandwidth.kernel
a character string giving the smoothing kernel to be used. This must partially match one of
"gaussian"
,"rectangular"
,"triangular"
,"epanechnikov"
,"biweight"
,"cosine"
or"optcosine"
, with default"gaussian"
, and may be abbreviated to a unique prefix (single letter)."cosine"
is smoother than"optcosine"
, which is the usual ‘cosine’ kernel in the literature and almost MSE-efficient. However,"cosine"
is the version used by S.window
a character string giving the smoothing kernel to be used. This must partially match one of
"gaussian"
,"rectangular"
,"triangular"
,"epanechnikov"
,"biweight"
,"cosine"
or"optcosine"
, with default"gaussian"
, and may be abbreviated to a unique prefix (single letter)."cosine"
is smoother than"optcosine"
, which is the usual ‘cosine’ kernel in the literature and almost MSE-efficient. However,"cosine"
is the version used by S.weights
numeric vector of non-negative observation weights, hence of same length as
x
. The defaultNULL
is equivalent toweights = rep(1/nx, nx)
wherenx
is the length of (the finite entries of)x[]
.width
this exists for compatibility with S; if given, and
bw
is not, will setbw
towidth
if this is a character string, or to a kernel-dependent multiple ofwidth
if this is numeric.give.Rkern
logical; if true, no density is estimated, and the ‘canonical bandwidth’ of the chosen
kernel
is returned instead.n
the number of equally spaced points at which the density is to be estimated. When
n > 512
, it is rounded up to a power of 2 during the calculations (asfft
is used) and the final result is interpolated byapprox
. So it almost always makes sense to specifyn
as a power of two.from
the left and right-most points of the grid at which the density is to be estimated; the defaults are
cut * bw
outside ofrange(x)
.to
the left and right-most points of the grid at which the density is to be estimated; the defaults are
cut * bw
outside ofrange(x)
.cut
by default, the values of
from
andto
arecut
bandwidths beyond the extremes of the data. This allows the estimated density to drop to approximately zero at the extremes.
- title
Character: plot title
- subtitle
Character: plot subtitle
- type
Character:
density
,boxplot
orviolin
plot- invertAxes
Boolean: plot X axis as Y and vice-versa?
- psi
Boolean: are
data
composed of PSI values? IfNULL
,psi = TRUE
if alldata
values are between 0 and 1- rugLabels
Boolean: plot sample names in the rug?
- rugLabelsRotation
Numeric: rotation (in degrees) of rug labels; this may present issues at different zoom levels and depending on the proximity of
data
values- legend
Boolean: show legend?
- valueLabel
Character: label for the value (by default, either
Inclusion levels
orGene expression
)
Details
Argument groups
can be either:
a list of sample names, e.g.
list("Group 1"=c("Sample A", "Sample B"), "Group 2"=c("Sample C")))
a character vector with the same length as
data
, e.g.c("Sample A", "Sample C", "Sample B")
.
See also
Other functions to perform and plot differential analyses:
diffAnalyses()