plot Mean-variance trend after voom and after final linear fit

plot Mean-variance trend after voom and after final linear fit

plot_mean_var(proc_data, span = 0.5)

Arguments

proc_data

processed data returned by process_data()

span

num, span for lowess()

Value

comparison plot of mean-variance of voom and final model

Examples

data("im_data_6")
proc_data <- process_data(
  im_data_6,
  group_col = "celltype:ch1",
  target_group = "NK"
)
#>        NK-Neutrophils NK-Monocytes NK-B.cells NK-CD4 NK-CD8
#> Down             4009         3944       3146   2694   2153
#> NotSig           1476         2678       4405   4985   6183
#> Up               4926         3789       2860   2732   2075
plot_mean_var(proc_data)