DensityThreshold-class

DensityThreshold

print,DensityThreshold-method

DensityThreshold-method

plot,DensityThreshold,missing-method

<code>DensityThreshold</code> contains output from the <code>dens</code> method findThreshold.

Provides a computational framework for analyzing mutations in
immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of
antigen-driven selection pressure, mutational load quantification, building of
somatic hypermutation (SHM) models, and model-dependent distance calculations.
Also includes empirically derived models of SHM for both mice and humans.
Citations:
Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>,
Yaari, et al (2012) <doi:10.1093/nar/gks457>,
Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>,
Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.

Susanna Marquez

shazam

Immunoglobulin Somatic Hypermutation Analysis

Mohamed Uduman

Namita Gupta

Julian Zhou

Nima Nouri

Noah Yann Lee

Ang Cui

Jason Vander Heiden

Gur Yaari

Steven Kleinstein

DensityThreshold-class function

<dl><dt>x</dt>
<dd>DensityThreshold object</dd>
<dt>y</dt>
<dd>ignored.</dd>
<dt>...</dt>
<dd>arguments to pass to plotDensityThreshold.</dd></dl>

Arguments

<dl>
<dt><code>x</code></dt>
<dd>input distance vector with NA or infinite values removed.</dd></dl>
<dt><code>bandwidth</code></dt>
<dd>bandwidth value fit during density estimation.</dd>
<dt><code>xdens</code></dt>
<dd>x-axis (distance value) vector for smoothed density estimate.</dd>
<dt><code>ydens</code></dt>
<dd>y-axis (density) vector for smoothed density estimate.</dd>
<dt><code>threshold</code></dt>
<dd>distance threshold that separates two modes of the input distribution.</dd>

Slots

Output of the dens method of findThreshold — DensityThreshold-class

<dl>

<dt>x</dt>
<dd>DensityThreshold object</dd>


<dt>y</dt>
<dd>ignored.</dd>


<dt>...</dt>
<dd>arguments to pass to plotDensityThreshold.</dd>

</dl>

<dl>
<dt><code>x</code></dt>
<dd>input distance vector with NA or infinite values removed.</dd>


<dt><code>bandwidth</code></dt>
<dd>bandwidth value fit during density estimation.</dd>


<dt><code>xdens</code></dt>
<dd>x-axis (distance value) vector for smoothed density estimate.</dd>


<dt><code>ydens</code></dt>
<dd>y-axis (density) vector for smoothed density estimate.</dd>


<dt><code>threshold</code></dt>
<dd>distance threshold that separates two modes of the input distribution.</dd>


</dl>

DensityThreshold-class: Output of the `dens` method of findThreshold

Description

Usage

Arguments

Slots

See Also