gbmLabel | R Documentation |
Returns the final label assignments for a parameter using a gradient boosting machine
gbmLabel(
x,
type = c("bead", "doublet", "debris", "dead"),
loss = c("auc", "class"),
n = 4000,
standardize = TRUE
)
x |
A |
type |
Identifies the type of label that is being modeled. Must be 'bead', 'doublet', 'debris', or 'dead'. |
loss |
Specifies the type of loss used to tune the GBM. Can be either "auc" for the area under the curve or "class" for classification error. |
n |
number of observations in training dataset. |
standardize |
Indicates if the data should be standardized. Because the data are on different scales, it should be standardized for this analysis. |
gbmLabel
uses a gradient boosting machine to compute the final labels
for the specified parameter type (bead, doublet, debris, or dead). This step
cannot be completed until the corresponding initialization function
(initialBead
, initialDebris
, initialDoublet
, or
initialDead
) is done on the SingleCellExperiment
created by
readCytof
.
The gbm is tuned using eztune
and then predicted
values are computed for all of the events in x
. If the predicted
probability for the label type is greater than 0.5, the label is changed to
the specified type. However, if an observation already has a label other
than 'cell' in the label
variable, it will not be changed. The
predicted probabilities for all of the observations are stored in the
variable associated with that type in the probs
object of x
for further analysis. Thus, it is possible to have a probability greater
than 0.5 for 'debris' but still have a label of 'bead' if an observation
was classified as a bead prior to classifying the debris.
An updated SingleCellExperiment
is returned with the labels
for the parameter of interest (bead, doublet, debris, or dead) added to
the label
object of the SingleCellExperiment
and the
probabilities for the event type added to the probs
object of the
SingleCellExperiment
.
data("raw_data", package = "CATALYST")
sce <- readCytof(raw_data, beads = "Beads", viability = c("cisPt1", "cisPt2"))
sce <- initialBead(sce)
sce <- gbmLabel(sce, type = "bead", loss = "auc")
head(probs(sce))
table(label(sce))
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