prepare_regressor_data

Helper function to create regressor data matrix, handling both regular
and non-regularized parameters if present

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

prepare_regressor_data function

<dl><dt>vst_out</dt>
<dd>vst object containing model_str and model_pars_nonreg</dd>
<dt>cell_attr</dt>
<dd>Data frame of cell attributes</dd></dl>

Arguments

Prepare regressor data from vst object and cell attributes — prepare_regressor_data

<dl>

<dt>vst_out</dt>
<dd>vst object containing model_str and model_pars_nonreg</dd>


<dt>cell_attr</dt>
<dd>Data frame of cell attributes</dd>

</dl>

prepare_regressor_data: Prepare regressor data from vst object and cell attributes

Description

Usage

Value

Arguments