Annotation {cytometree} | R Documentation |
Annotates cell populations found using CytomeTree.
Description
Annotates cell populations found using CytomeTree.
Usage
Annotation(
CytomeTreeObj,
K2markers = NULL,
K3markers = NULL,
plot = TRUE,
t = 0.2,
remove_outliers_inplot = TRUE,
center_fun = c("median", "mean")
)
Arguments
CytomeTreeObj |
An object of class CytomeTree. |
K2markers |
A vector of class character where the names of
the markers for which 2 levels of expression are sought can be specified.
Default is |
K3markers |
A vector of class character where the names of
the markers for which 3 levels of expression are sought can be specified.
Default is |
plot |
A logical value indicating whether or not to plot the
partitioning in 1, 2 or 3 groups for each marker. Default is |
t |
A real positive-or-null number used for comparison with the normalized AIC computed to compare the fits of the marginal distributions obtained by one normal distribution and by a mixture of two or three normal. For markers used in the tree, the algorithm compares the fits obtained by a mixture of two and three normal distributions. Default value is .2. A higher value leads to a smaller number of expression levels per marker. |
remove_outliers_inplot |
a logical flag indicating whether the y-axis
should be scaled by removing outliers or not. Default is |
center_fun |
a character string either 'median' or 'mean' indicating based
on which summary the populations should be ordered. Default is |
Details
The algorithm is set to find the partitioning in 1, 2 or 3 groups of cell populations found using CytomeTree. In an unsupervised mode, it minimizes the within-leaves sum of squares of the observed values on each marker and computes the normalized AIC to compare the fits of the marginal distributions obtained by one normal distribution and by a mixture of two or three normal.For markers used in the tree, the algorithm compares the fits obtained by a mixture of two and three normal distributions.
Value
A data.frame
containing the annotation of each
cell population.
Author(s)
Chariff Alkhassim, Boris Hejblum