Description Usage Arguments Value Category Filter See Also Examples
This function fits the COMPASS
model.
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data 
An object of class 
treatment 
An R expression, evaluated within the metadata, that
returns 
control 
An R expression, evaluated within the metadata, that
returns 
subset 
An expression used to subset the data. We keep only the samples
for which the expression evaluates to 
category_filter 
A filter for the categories that are generated. This is a
function that will be applied to the treatment counts matrix generated from
the intensities. Only categories meeting the 
filter_lowest_frequency 
A number specifying how many of the least expressed markers should be removed. 
filter_specific_markers 
Similar to 
model 
A string denoting which model to fit; currently, only
the discrete model ( 
iterations 
The number of iterations (per 'replication') to perform. 
replications 
The number of 'replications' to perform. In order to conserve memory, we only keep the model estimates from the last replication. 
keep_original_data 
Keep the original 
verbose 
Boolean; if 
dropDegreeOne 
Boolean; if 
... 
Other arguments; currently unused. 
A COMPASSResult
is a list with the following components:
fit 
A list of various fitted parameters resulting from the

data 
The data used as input to the 
orig 
If 
The fit
component is a list with the following components:
alpha_s 
The hyperparameter shared across all subjects under the
stimulated condition. It is updated through the 
A_alphas 
The acceptance rate of 
alpha_u 
The hyperparameter shared across all subjects under the
unstimulated condition. It is updated through the 
A_alphau 
The acceptance rate of 
gamma 
An array of dimensions 
mean_gamma 
A matrix of mean response rates. Each cell denotes
the mean response of individual 
A_gamma 
The acceptance rate for the gamma. Each element
corresponds to the number of times an individual's 
categories 
The category matrix, showing which categories entered the model. 
model 
The type of model called. 
posterior 
Posterior measures from the sample fit. 
call 
The matched call used to generate the model fit. 
The data
component is a list with the following components:
n_s 
The counts matrix for stimulated samples. 
n_u 
The counts matrix for unstimulated samples. 
counts_s 
Total cell counts for stimulated samples. 
counts_u 
Total cell counts for unstimulated samples. 
categories 
The categories matrix used to define which categories will enter the model. 
meta 
The metadata. Note that only individuallevel metadata will be kept; samplespecific metadata is dropped. 
sample_id 
The name of the vector in the metadata used to identify the samples. 
individual_id 
The name of the vector in the metadata used to identify the individuals. 
The orig
component (included if keep_original_data
is
TRUE
) is the COMPASSContainer
object used in the model
fit.
The category filter is used to exclude categories (combinations of
markers expressed for a particular cell) that are expressed very rarely.
It is applied to the treatment
counts matrix, which is a
N
samples by K
categories matrix. Those categories which
are mostly unexpressed can be excluded here. For example, the default
criteria,
category_filter=function(x) colSums(x > 5) > 2
indicates that we should only retain categories for which at least three samples had at least six cells expressing that particular combination of markers.
COMPASSContainer
, for constructing the data object
required by COMPASS
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