quantKnn function

Noise-related quantaties of local pruned k-nearest neighbourhoods

This function computes a number of noise-related quantities for all pruned k-nearest neighbourhoods.

quantKnn(res, noise, object, pvalue = 0.01, minN = 5, no_cores = NULL)

Arguments

• res: List object with k nearest neighbour information returned by pruneKnn function.
• noise: List of noise parameters returned by compTBNoise.
• object: SCseq class object.
• pvalue: Positive real number between 0 and 1. All nearest neighbours with link probability < pvalue are discarded. Default is 0.01.
• minN: Positive integer number. Noise inference is only done for k-nearest neighbourhoods with at least minN neighbours remaining after pruning.
• no_cores: Positive integer number. Number of cores for multithreading. If set to NULL then the number of available cores minus two is used. Default is NULL.

Returns

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.