quantKnn {RaceID} | R Documentation |
Noise-related quantaties of local pruned k-nearest neighbourhoods
Description
This function computes a number of noise-related quantities for all pruned k-nearest neighbourhoods.
Usage
quantKnn(res, noise, object, pvalue = 0.01, minN = 5, no_cores = NULL)
Arguments
res |
List object with k nearest neighbour information returned by |
noise |
List of noise parameters returned by |
object |
|
pvalue |
Positive real number between 0 and 1. All nearest neighbours with link probability |
minN |
Positive integer number. Noise inference is only done for k-nearest neighbourhoods with at least |
no_cores |
Positive integer number. Number of cores for multithreading. If set to |
Value
List object with eight components:
noise.av |
Vector of biological noise average across all genes for each k-nearest neighbourhood. |
noise.ratio |
Vector of ratio between total noise and technical noise averaged across all genes for each k-nearest neighbourhood. |
local.corr |
Vector of average Spearman's correlation coefficient between all cell in a pruned k-nearest neighourhood. |
umi |
Vector of total UMI counts for all cells. |