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> for more details.

Variance Stabilizing Transformations for Single Cell UMI Data

package-ubuntu-20.04-r-4.0.5#cran#sctransform-0.3.2

<table summary="R argblock">
<tr valign="top">
<td><code>y</code></td>
<td>
<p>Dependent variable</p>
</td>
</tr>
<tr valign="top">
<td><code>x</code></td>
<td>
<p>Independent variable</p>
</td>
</tr>
<tr valign="top">
<td><code>th</code></td>
<td>
<p>Outlier score threshold</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#sctransform-0.3.2#docs#is_outlier

is_outlier

Description

Usage

Arguments

Value

sctransform

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`y`	Dependent variable
`x`	Independent variable
`th`	Outlier score threshold