`R/mc_outliers.r`

`mcell_mc_split_filt.Rd`

Running intra-metacell clustering on each metacell, identifying splits if existing. Also remove cells with outlier expression from each metacell. Note that this can in many case eliminate doublets as outliers - but may be insffucieint as doublets may constitute homogeneous metacells in large datasets.

```
mcell_mc_split_filt(
new_mc_id,
mc_id,
mat_id,
T_lfc,
plot_mats = T,
dirichlet = F
)
```

- new_mc_id
id of metacells to create

- mc_id
id of source metacell object

- mat_id
id of umi matrix

- plot_mats
if this is true, a heatmap will be generated for each metacell

- dirichlet
if this is true, the distance metric to be used for splitting is dirichlet on the downsampled umi counts. Otherwise (and by default), the correlation between log(1+umi) of the downsampled matrix will be used. Note that downsampling is done given the miminum depth of each metacell, seperately.