A building block of the main functions. To evaluate each metacell partition and optimize metacell partitioning based on the output permutation results (TabMC) and thresholds (threshold)
mcRigor_tradeoff.RdA building block of the main functions. To evaluate each metacell partition and optimize metacell partitioning based on the output permutation results (TabMC) and thresholds (threshold)
Usage
mcRigor_tradeoff(
TabMC,
threshold,
D_bw = 10,
optim_method = c("tradeoff", "dub_rate_large", "dub_rate_small"),
dub_rate = 0.1,
weight = 0.5,
draw = T
)Arguments
- TabMC
A dataframe containing the permutation results. Saved in the previous steps
- threshold
A dataframe containing the dubious metacell detection thresholds given by mcRigor_threshold
- D_bw
A boolean indicating whether to smooth the dubious rate with respect to metacell size
- optim_method
The method used for granularity level optimization. Default is trading off between sparsity and dubious rate
- dub_rate
If tradeoff is not used for optimization, what is highest acceptable dubious rate
- weight
The weight for dubious rate in the tradeoff.
- draw
A boolean indicating whether to visualize the mcRigor results