batch_correct: Run batch correction on data

In shdam/cyCombine: Robust integration of single-cell cytometry datasets within and across technologies

Run batch correction on data

Description

This is a wrapper function for the cyCombine batch correction workflow. To run the workflow manually, type "batch_correct" to see the source code of this wrapper and follow along or read the vignettes on the GitHub page https://github.com/biosurf/cyCombine.

Usage

batch_correct(
  df,
  label = NULL,
  xdim = 8,
  ydim = 8,
  rlen = 10,
  parametric = TRUE,
  seed = 473,
  covar = NULL,
  anchor = NULL,
  markers = NULL,
  norm_method = "scale",
  ties.method = "average"
)

Arguments

df	tibble with expression values
label	The cluster or cell type label. Either as a column name or vector.
xdim	The x-dimension size of the SOM.
ydim	The y-dimension size of the SOM.
rlen	Number of times the data is presented to the SOM network
parametric	Default: TRUE. If TRUE, the parametric version of ComBat is used. If FALSE, the non-parametric version is used.
seed	The seed to use when creating the SOM.
covar	The covariate ComBat should use. Can be a vector or a column name in the input tibble. If NULL, no covar will be used
anchor	Experimental: A column or vector specifying which samples are replicates and which are not. If specified, this column will be used as a covariate in ComBat. Be aware that it may be confounded with the condition.
markers	Markers to normalize. If NULL, markers will be found using the get_markers function.
norm_method	Normalization method. Should be either 'rank', 'scale' or 'qnorm'. Default: 'scale'
ties.method	The method to handle ties, when using rank. Default: 'average'. See ?rank for other options.

See Also

Other batch: correct_data(), create_som(), normalize(), quantile_norm()

Examples

## Not run: 
corrected <- uncorrected %>%
  batch_correct(markers = markers,
  covar = "condition")
  
## End(Not run)

shdam/cyCombine documentation built on June 12, 2022, 11:29 p.m.