celdaProbabilityMap: Renders probability and relative expression heatmaps to...
In compbiomed/celda: CEllular Latent Dirichlet Allocation
Description
Usage
Arguments
Value
Examples
Description
It is often useful to visualize to what degree each feature influences each
cell cluster. This can also be useful for identifying features which may
be redundant or unassociated with cell clustering.
Usage
1
celdaProbabilityMap(counts, celda.mod, ...)
Arguments
counts
Integer matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate 'celda.mod'.
celda.mod
Celda object of class "celda_C" or "celda_CG".
...
Additional parameters.
Value
A grob containing the specified plots
Examples
1
celdaProbabilityMap(celda.CG.sim$counts, celda.CG.mod)
compbiomed/celda documentation built on May 25, 2019, 3:58 a.m.
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Description Usage Arguments Value Examples
Description
It is often useful to visualize to what degree each feature influences each cell cluster. This can also be useful for identifying features which may be redundant or unassociated with cell clustering.
Usage
1 | celdaProbabilityMap(counts, celda.mod, ...)
|
Arguments
counts |
Integer matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate 'celda.mod'. |
celda.mod |
Celda object of class "celda_C" or "celda_CG". |
... |
Additional parameters. |
Value
A grob containing the specified plots
Examples
1 | celdaProbabilityMap(celda.CG.sim$counts, celda.CG.mod)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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