normalize: Batch-wise normalization of data

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

Batch-wise normalization of data

Description

This function normalizes the data in a batch-wise manner. The purpose is to minimize the impact of batch correction when clustering the data prior to batch correction. Three normalisation methods are implemented: Z-score, Rank, and Quantile normalization. Z-score is recommended in cases where batches from a single study/experiment is merged. Rank is recommend in cases where data from different studies/experiments are merged. Quantile is not recommended.

Usage

normalize(df, markers = NULL, norm_method = "scale", ties.method = "average")

Arguments

df	tibble with expression values
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: batch_correct(), correct_data(), create_som(), quantile_norm()

Examples

## Not run: 
df_normed <- df %>%
  normalize()
  
## End(Not run)

biosurf/cyCombine documentation built on May 23, 2024, 4:07 a.m.