SCIBER {SCIBER}

Batch effect removal with SCIBER

Description

Batch effect removal with SCIBER

Usage

SCIBER(
  input_batches,
  ref_index = NULL,
  batches_meta_data = NULL,
  omega = 0.5,
  h_fisher = 75,
  n_core = parallel::detectCores(),
  seed = 7,
  k = NULL
)

Arguments

input_batches

A list contains all the pre-processed matrices with dimension of n_genes*n_cells.

ref_index

The index of the reference batch in the object "input_batches"

batches_meta_data

A list contains the meta data for all the batches. The order should be consistent with that in "input_batches". Each meta data contains three columns, "cell_id", "cell_type", and "dataset". "dataset" indicates which batch the data comes from. The row names of meta data should match the column names of batch.

omega

A list of proportion of matched clusters or a single value between 0 and 1 applied to all query batches.

h_fisher

The number of marker genes used for Fisher exact test.

n_core

Specify the number of cores otherwise use all the available cores.

seed

random seed.

k

Number of clusters used for K-means. If not provided, the default is k = the square root of n_0, where n_0 is the number of cells in the reference batch.

Value

A list which contains the reference and batch-effect-corrected batches. The order is the same as that in input_batches.

Examples

data(HumanDC)
exp <- HumanDC[["exp"]]
meta <- HumanDC[["metadata"]]
omega <- c()
omega[[1]] <- 0.5
res <- SCIBER(input_batches = exp, ref_index = 1,
batches_meta_data = meta, omega = omega, n_core = 1)