flowSets
the idea is to
horizontally stack plots of density estimates for all frames in the
flowSet
for one or several flow parameters. In the latter case, each
parameter will be plotted in a separate panel, i.e., we implicitly condition
on parameters.## S3 method for class 'formula,flowSet':
densityplot(x, data, ...)prepanel.densityplot.flowset.stack(x, y, frames, overlap = 0.3, subscripts,
..., which.channel)
panel.densityplot.flowset.stack(x, y, darg = list(n = 50, na.rm = TRUE),
frames, channel, overlap = 0.3, channel.name, filter = NULL,
fill = superpose.polygon$col, lty = superpose.polygon$lty,
lwd = superpose.polygon$lwd, alpha = superpose.polygon$alpha,
col = superpose.polygon$border, groups = NULL, refline = NULL,
margin = 0.005, stats = FALSE, pos = 0.5, digits = 2, abs = FALSE,
fitGate = TRUE, checkName = TRUE, plotType = "densityplot",
hist.type = "density", breaks = "Sturges", gp, ...)
## S3 method for class 'formula,flowFrame':
densityplot(x, data, overlay = NULL, ...)
## S3 method for class 'formula,view':
densityplot(x, data, ...)
## S3 method for class 'formula,flowSet':
histogram(x, data, plotType, ...)
## S3 method for class 'formula,flowFrame':
histogram(x, data, ...)
factor ~
parameter
, where factor
can be any of the phenotypic factors in the
phenoData
slot or an appropriate factor object and parameter
is a flow parameter. Panels for multiple parameters are drawn if the formula
structure is similar to factor ~ parameter1 + parameter2
, and
factor
can be missing, in which case the sample names are used as
y-variable. To facilitate programatic access, the formula can be of special
structure factor ~ .
, in which case the optional channel
argument is considered for parameter selection. For the workflow methods,
x
can also be one of the several workflow objects.flowFrame
method.darg
gets passed on to density
.filter
,
filterResult
or
filterResultList
object or a list
of such objects of the same length as the flowSet
. If applicable, the
gate region will be superiposed on the density curves using color shading.
The software will figure out whether the filter
needs to be evaluated
in order to be plotted (in which case providing a filterResult
can
speed things up considerably).lattice
-like par.setting
and flowViz.par.set
customization. The relevant parameter category for density plots is
gate.density
with available parameters col
, fill
,
lwd
, alpha
and lty
. See
flowViz.par.set
for details.flowSet
, or a factor.panel.abline
.[0,1]
.
When 'FALSE', it doesn't do anything to the margin events. When Numeric
value, it indicates margin events by horizontal bars. The value of
margin
is interpreted as the proportion of events on the margin over
which the bars are added. E.g., a value of 0,5
means to indicate
margin events if there are more than 0.5
times the total number of
events. 1
means to ignore margin events completetly. For 0
bars are added even if there is only a single margin event.logical
scalar indicating whether to display the
gate as fitted 1d density gate region or simply display the gate boundaries
using vertical lines. The latter would be helpful to display the gate when
the gated density region is too small to see.logical
scalar indicating whether to validity
check the channel name. Default is TRUE, which consider '(' as invalid
character in channel namespar.settings
for
customization of a single call or flowViz.par.set
for customization
of session-wide defaults.x
is of structurefactor ~ .
.xyplot
xyplot
axis.grid
library(flowStats)
data(GvHD)
GvHD <- GvHD[pData(GvHD)$Patient %in% 6:7]
densityplot(~ `FSC-H`, GvHD)
densityplot(~ `FSC-H` + `SSC-H`, GvHD)
densityplot(~ ., GvHD[1:3])
## include a filter
densityplot(~ `FSC-H`, GvHD, filter=curv1Filter("FSC-H"))
#display the gate by its boundaries with statistics
densityplot(~ `FSC-H`, GvHD[1:2], filter=curv1Filter("FSC-H"),fitGate=FALSE,stats=TRUE)
## plot a single flowFrame
densityplot(~ `SSC-H`, GvHD[[1]], margin=FALSE)
## plot histogram
histogram(~ `SSC-H`, GvHD[[1]]) #default type is 'density'
#change the type to 'count' and adjust breaks
histogram(~ `SSC-H`, GvHD[[1]], margin=FALSE, type = "count", breaks = 50)
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