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getNeighborMatrix

Establish rough neighbor matching between samples given their projections in a common space


Description

Establish rough neighbor matching between samples given their projections in a common space

Usage

getNeighborMatrix(
  p1,
  p2,
  k,
  k1 = k,
  matching = "mNN",
  metric = "angular",
  l2.sigma = 1e+05,
  cor.base = 1,
  min.similarity = 1e-05
)

Arguments

p1

projection of sample 1

p2

projection of sample 2

k

neighborhood radius

k1

neighborhood radius

matching

string mNN (default) or NN (default='mNN')

metric

string Distance type (default: "angular", can also be 'L2')

l2.sigma

numeric L2 distances get transformed as exp(-d/sigma) using this value (default=1e5)

cor.base

numeric (default=1)

min.similarity

minimal similarity between two cells, required to have an edge

Value

matrix with the similarity (!) values corresponding to weight (1-d for angular, and exp(-d/l2.sigma) for L2)


conos

Clustering on Network of Samples

v1.4.0
GPL-3
Authors
Viktor Petukhov [aut], Nikolas Barkas [aut], Peter Kharchenko [aut], Weiliang Qiu [ctb], Evan Biederstedt [aut, cre]
Initial release

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