ProjectSNN: Calculates shared nearest neighbors between samples (columns)...

In yanwu2014/swne: Similarity Weighted Nonnegative Embedding: A method for visualizing high dimensional datasets

Calculates shared nearest neighbors between samples (columns) in a test matrix and samples in a training matrix Adapted from Seurat

Description

Calculates shared nearest neighbors between samples (columns) in a test matrix and samples in a training matrix Adapted from Seurat

Usage

ProjectSNN(
  test.data,
  train.data,
  n.pcs = NULL,
  features.use = NULL,
  k = 30,
  k.scale = 10,
  prune.SNN = 1/15,
  print.output = T
)

Arguments

test.data	Test data
train.data	Training data
features.use	Subset of features to use (default is all features)
k	Number of nearest neighbors
k.scale	k*k.scale is the number of nearest neighbors to calculate shared nearest neighbors for
prune.SNN	Minimum fraction of shared nearest neighbors
print.output	Prints progress bar if true
pcs.use	If not null, run PCA on training data and project test data before computing SNN

Value

A n.test x n.train matrix with the shared nearest neighbors between test and training data

yanwu2014/swne documentation built on Aug. 5, 2023, 4:42 a.m.