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)
MarkerListmatrix 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.