is_outlier

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

is_outlier function

<dl><dt>y</dt>
<dd>Dependent variable</dd>
<dt>x</dt>
<dd>Independent variable</dd>
<dt>th</dt>
<dd>Outlier score threshold</dd></dl>

Arguments

Identify outliers — is_outlier

<dl>

<dt>y</dt>
<dd>Dependent variable</dd>


<dt>x</dt>
<dd>Independent variable</dd>


<dt>th</dt>
<dd>Outlier score threshold</dd>

</dl>

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is_outlier: Identify outliers

Description

Usage

Value

Arguments