Return average variance under negative binomial model
This is based on the formula var = mu + mu^2 / theta
get_model_var( vst_out, cell_attr = vst_out$cell_attr, use_nonreg = FALSE, bin_size = 256, verbosity = 2, verbose = NULL, show_progress = NULL )
vst_out |
The output of a vst run |
cell_attr |
Data frame of cell meta data |
use_nonreg |
Use the non-regularized parameter estimates; boolean; default is FALSE |
bin_size |
Number of genes to put in each bin (to show progress) |
verbosity |
An integer specifying whether to show only messages (1), messages and progress bars (2) or nothing (0) while the function is running; default is 2 |
verbose |
Deprecated; use verbosity instead |
show_progress |
Deprecated; use verbosity instead |
A named vector of variances (the average across all cells), one entry per gene.
vst_out <- vst(pbmc, return_cell_attr = TRUE) res_var <- get_model_var(vst_out)
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