The method beeswarm
for MarkerList
objects
draws, separately for each cell-type, a stripchart of the
markers' expression values in a reference data,
highlighting the expression of their respective
associated -- generally pure -- samples.
The method stripchart.MarkerList
is an alias for
beeswarm.MarkerList
.
profplot
is vectorised over arguments scale
and legend.
screeplot
plots the following diagnostic plots:
hist
plots the histogram of numeric scores
associated with each marker in a marker list, if any.
S3 (MarkerList) `beeswarm`(x, data, types = NULL, tcol = "red", otcol = "#00000090", las = 2, fold = FALSE, method = "square", corral = "wrap", pch = 19, pwcol = NULL, ylab = if (fold) "Fold changes" else "Expression values", ...) S3 (MarkerList) `stripchart`(x, data, types = NULL, tcol = "red", otcol = "#00000090", las = 2, fold = FALSE, method = "square", corral = "wrap", pch = 19, pwcol = NULL, ylab = if (fold) "Fold changes" else "Expression values", ...) S3 (MarkerList) `profplot`(x, y, groups = NULL, scale = FALSE, col = NULL, legend = FALSE, split = TRUE, ylab = NA, labels = NULL, ..., restore.gpar = TRUE) S3 (MarkerList) `screeplot`(x, data = NULL, breakdown = FALSE, range = NULL, xlab = NULL, ylab = NULL, main = NULL, ..., plot = TRUE) S3 (MarkerList) `hist`(x, range = NULL, split = FALSE, xlab = "Marker scores", main = "Histogram of marker scores", ..., restore.gpar = TRUE)
MarkerList
matrix
or an
ExpressionSet
object containing expression values
from samples.factor
giving the cell-type of each
samplepar
.beeswarm
, matplot
,
barplot
, hist
or
plot
, depending on the main calling
function.split=FALSE
, this is a logical
that indicates if the marker expression profiles should
be scaled into relative contribution (i.e., sum up to
one), as in profplot
.
When split is not FALSE
, then
scale=TRUE
indicates that the profiles should be
normalised with the mean expression profile of all
markers. If a single numeric, then it indicates the index
of a specific marker that is used to normalise the
expression profiles of other markers. Separate indexes
for each cell type can be passed as a numeric vector or a
list.
This is useful to highlight groups of markers that should
have equivalent cell-specific expression levels, given
the -- mixed -- expression data in y
. These groups
are likely to provide better proportion/cell-specific
estimates.
Note: values are recycled if necessary.split=FALSE
, or for each marker in each cell type
otherwise.par(mfrow=split)
.split=TRUE
.hist
, or in screeplot
when
data=NULL
, it indicates a range over which the
scores are used to computing the histogram. If
NULL
, then all values are used (Note: this might
take a bit of time for long marker lists if
breakdown=TRUE
). Otherwise it must be a 2-long
numeric vector giving the interval of values to use.
If data
is not NULL
, it indicates whichNULL
, then it must
be either a range of valuesx
of legend
, that
specifies the position of the legend.When data=NULL
and breakdown
is not
FALSE
this function returns a list with the result
from the breakdown barplot and the breakdown (in element
breakdown).
When data
is not NULL
, a
MarkerList-class
object made of the set of
markers that achieve the least condition number is
returned.