perform.singleR.annotation: Performs automated cell annotation on query datasets using...

In connorhknight/IBRAP: Integrated Benchmarking scRNA-seq Analytical Pipeline (IBRAP)

Performs automated cell annotation on query datasets using reference data

Description

SingleR iterates through singular cells and iterates through probabilitiy comparisons to identify which cell type the query cell is likely to be. If a probably cell type cannot be discovered then

Usage

perform.singleR.annotation(
  object,
  assay = "RAW",
  slot = "counts",
  ref,
  log.transform.query = TRUE,
  tpm.transform.query = FALSE,
  log.transform.ref = TRUE,
  tpm.transform.ref = FALSE,
  ref.labels,
  column.suffix = "1",
  verbose = FALSE,
  seed = 1234,
  ...
)

Arguments

object	IBRAP S4 class object
assay	Character. String containing indicating which assay to use
slot	Character. String indicating which slot within the assay should be sourced
ref	AnyMatrix. A matrix of the reference datasets, if data is end-bias then it should be log normalised, if it is full-length then it requires tpm normalisation. Both can be completed within this function.
ref.labels	Vector. The cluster assignments for the reference data. Default = NULL
column.suffix	Character. A suffix to append the end of the new metadata columns if this functiuons is to be used multiple times. Default = '1'
verbose	Logical Should function messages be printed?
seed	Numeric. What should the seed be set as. Default = 1234
...	arguments to be passed to singleR::SingleR
log.transform	Boolean. Should the reference data be log transformed. Default = TRUE
tpm.transform	Boolean. Should the reference data be tpm normalised. Default = FALSE

Value

Produces a new 'methods' assay containing normalised, scaled and HVGs.

Examples

object <- perform.singleR.annotation(object = object, ref = reference_matrix, ref.labels = metadata_reference$celltype)

connorhknight/IBRAP documentation built on March 9, 2023, 7:01 p.m.