adj_CDF_logit

This function returns a matrix of a novel data representation with the same dimension as input data matrix.

Useful to visualize the Poissoneity (an independent Poisson statistical framework,
where each RNA measurement for each cell comes from its own independent Poisson distribution) of
Unique Molecular Identifier (UMI) based single cell RNA sequencing (scRNA-seq) data, and explore
cell clustering based on model departure as a novel data representation.

Yue Pan

scpoisson

Single Cell Poisson Probability Paradigm

Justin Landis

Dirk Dittmer

James S. Marron

Di Wu

adj_CDF_logit function

<dl><dt>data</dt>
<dd>A UMI count data matrix with genes as rows and cells as columns or an S3 object for class 'scppp'.</dd>
<dt>change</dt>
<dd>A numeric value used to correct for exactly 0 and 1 before logit transformation.
Any values below <code>change</code> are set to be <code>change</code> and
any values above \(1- change\) are set to be \(1- change\).</dd>
<dt>...</dt>
<dd>not used.</dd></dl>

Arguments

A novel data representation based on Poisson probability — adj_CDF_logit

<dl>

<dt>data</dt>
<dd>A UMI count data matrix with genes as rows and cells as columns or an S3 object for class 'scppp'.</dd>


<dt>change</dt>
<dd>A numeric value used to correct for exactly 0 and 1 before logit transformation.
Any values below <code>change</code> are set to be <code>change</code> and
any values above \(1- change\) are set to be \(1- change\).</dd>


<dt>...</dt>
<dd>not used.</dd>

</dl>

adj_CDF_logit: A novel data representation based on Poisson probability

Description

Usage

Value

Arguments

Details

Examples