umify_data

<p>The functions have been trained on various public data sets and relate quantile
values to log-counts. Here the expected values at various points are given.</p>

datasets

A normalization method for single-cell UMI count data using a
variance stabilizing transformation. The transformation is based on a
negative binomial regression model with regularized parameters. As part of the
same regression framework, this package also provides functions for
batch correction, and data correction. See Hafemeister and Satija (2019)
<doi:10.1186/s13059-019-1874-1>, and Choudhary and Satija (2022) <doi:10.1186/s13059-021-02584-9>
for more details.

Saket Choudhary

sctransform

Variance Stabilizing Transformations for Single Cell UMI Data

Christoph Hafemeister

Rahul Satija

umify_data function

<p>A list of length two. The first element is a data frame with group, quantile and 
log-counts values. The second element is a vector of breaks to be used with cut to group
observations.</p>

umify_data: Transformation functions for umify

Description

Usage

Arguments

Format