umify: Quantile normalization of cell-level data to match typical...

In sctransform: Variance Stabilizing Transformations for Single Cell UMI Data

Quantile normalization of cell-level data to match typical UMI count data

Description

Quantile normalization of cell-level data to match typical UMI count data

Usage

umify(counts)

Arguments

counts

A matrix of class dgCMatrix with genes as rows and columns as cells

Value

A UMI-fied count matrix

Details

sctransform::vst operates under the assumption that gene counts approximately follow a Negative Binomial dristribution. For UMI-based data that seems to be the case, however, non-UMI data does not behave in the same way. In some cases it might be better to to apply a transformation to such data to make it look like UMI data. This function applies such a transformation function.

Cells in the input matrix are processed independently. For each cell the non-zero data is transformed to quantile values. Based on the number of genes detected a smooth function is used to predict the UMI-like counts.

The functions have be trained on various public data sets and come as part of the package (see umify_data data set in this package).

Examples

silly_example <- umify(pbmc)

sctransform documentation built on Oct. 19, 2023, 9:08 a.m.