calculate_alignment: Calculate the alginment score

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

Description

Calculate the alginment score per sample, per cluster and per dataset

Usage

calculate_alignment(
  X.list,
  k = NULL,
  balanced = F,
  min.sample.per.dataset = 100,
  dataset = NULL,
  labels = NULL,
  max.k = 50,
  seed = 0,
  verbose = F,
  pca = F
)

Arguments

X.list	a list of gene expression matrix per batch
k	integer, number of nearest neighbor to consider
balanced	boolean, whether to subset to balance the size of baches
min.sample.per.dataset	integer, minimum cells to sample per dataset (default 100)
dataset	factor/characteristic vector that indicate the batch of cells if len(X.list)==1
labels	factor/characteristic vector, cluster/cell type labels of the cells
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.

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