calculate_alignment_per_type: Calculate the alginment score

In pengminshi/cFIT: cFIT (common Factor Space Integration & Transfer)

Description

Calculate the alginment score per cluster, where the normalization is performed based on the per-group batch population ratios

Usage

calculate_alignment_per_type(
  X,
  dataset = NULL,
  labels = NULL,
  k = NULL,
  max.k = 50,
  seed = 0,
  verbose = F,
  pca = F
)

Arguments

X	ncell-by-ngene expression matrix
dataset	factor/characteristic vector that indicate the batch of cells
labels	factor/characteristic vector, cluster/cell type labels of the cells
k	integer, number of nearest neighbor to consider
max.k	integer, maximum number of nearest neighbors to consider (cap for large dataset)
seed	random seed
verbose	boolean scalar, whether to show extensive program logs (default TRUE)
pca	if pca!=F, perform pca first before calculating the pairwise distance

Value

A list containing

alignment.per.sample

a numeric vector, alignment score per cell

alignment.per.cluster

a numeric vector, alignment score per cluster. Only calculated with labels are provided

alignment.per.dataset

a numeric vector, alignment score per dataset.

alignment.per.dataset.cluster

numeric vector, alignment score per dataset per cluster

pengminshi/cFIT documentation built on July 11, 2021, 11:12 p.m.