train.cytonorm: train.cytonorm - Prepare reference data into a FlowSOM object

In sydneycytometry/Spectre: A computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry data.

Description

This function allows you to learn the conversions to use for batch alignment.

Usage

train.align()

Arguments

method	DEFAULT = 'cytonorm'. In future additional methods for batch alignment will be added.
cytonorm.goal	DEFAULT = 'mean'. Target values for alignment. Can be 'mean' for the average of all batches, or a specific batch can be selected.
cytonorm.nQ	DEFAULT = 101. Number of quantiles.
dir	DEFAULT = getwd(). Sets the working directory to operate from. Because this function involves some reading/writing of files, it's best to set this to somewhere static in case the active working directory moves to a subfolder, and then doesn't return because the function runs into an error.
mem.ctrl	DEFAULT = TRUE. Allows the function to clear held memory on occasion.
dat	NO DEFAULT. A data.table consisting of the 'refernece' data you will use to train the alignment algorithm
cellular.cols	NO DEFAULT. A vector of column names from the data.table that contain the markers to be aligned

Value

Returns the alignment model object, with an additional 'conversions' element added.

Author(s)

Thomas M Ashhurst, [e-mail]

References

Ashhurst, T. M., et al. (2019). https://www.ncbi.nlm.nih.gov/pubmed/31077106

Examples

align.model <- train.cytonorm()

sydneycytometry/Spectre documentation built on March 20, 2021, 2:15 a.m.