| gene_importances {SCORPIUS} | R Documentation | 
Calculate the importance of a feature
Description
Calculates the feature importance of each column in x in trying to predict the time ordering.
Usage
gene_importances(
  x,
  time,
  num_permutations = 0,
  ntree = 10000,
  ntree_perm = ntree/10,
  mtry = ncol(x) * 0.01,
  num_threads = 1,
  ...
)
Arguments
| x | A numeric matrix or a data frame with M rows (one per sample) and P columns (one per feature). | 
| time | A numeric vector containing the inferred time points of each sample along a trajectory as returned by  | 
| num_permutations | The number of permutations to test against for calculating the p-values (default: 0). | 
| ntree | The number of trees to grow (default: 10000). | 
| ntree_perm | The number of trees to grow for each of the permutations (default: ntree / 10). | 
| mtry | The number of variables randomly samples at each split (default: 1% of features). | 
| num_threads | Number of threads. Default is 1. | 
| ... | Extra parameters passed to  | 
Value
a data frame containing the importance of each feature for the given time line
Examples
dataset <- generate_dataset(num_genes=500, num_samples=300, num_groups=4)
expression <- dataset$expression
group_name <- dataset$sample_info$group_name
space <- reduce_dimensionality(expression, ndim=2)
traj <- infer_trajectory(space)
# set ntree to at least 1000!
gene_importances(expression, traj$time, num_permutations = 0, ntree = 1000)
[Package SCORPIUS version 1.0.9 Index]