buildKNN-methods: Build kNN graph.

In edroaldo/fusca: Framework for Unified Single-Cell Analysis

Build kNN graph.

Description

Create kNN graph using the PCA components and cell-cell similarities using the jaccard or invlog methods. Write graph to file.

Usage

buildKNN(
  object,
  assay.type = "RNA",
  k = 5,
  column.ann,
  num.pcs = 20,
  sim.type = "jaccard",
  filename = "graph_clusters.gml"
)

## S4 method for signature 'CellRouter'
buildKNN(
  object,
  assay.type = "RNA",
  k = 5,
  column.ann,
  num.pcs = 20,
  sim.type = "jaccard",
  filename = "graph_clusters.gml"
)

Arguments

object	CellRouter object.
assay.type	character; the type of data to use.
k	numeric; number of nearest neighbors to build a k-nearest neighbors graph for trajectory reconstruction.
column.ann	character; column in the metadata table specifying the transitions to be identified. For example, if 'population' is provided, transitions will be identified between clusters previously identified. However, sorted cell populations or customized states can also be used. Check our tutorials for detailed examples.
num.pcs	numeric; number of principal components that will define the space from where the kNN graph is identified. For example, if num.pcs = 10, the kNN graph will be created from a 10-dimensional PCA space.
sim.type	character; updates the kNN graph to encode cell-cell similarities using the jaccard or invlog methods.
filename	character; name of gml file containing the kNN graph.

Value

CellRouter object with the graph, ndata, and sampTab slots updated.

edroaldo/fusca documentation built on March 1, 2023, 1:43 p.m.