kOT_sim_OT

Perform optimal transport on somatic point mutations and kernel regression hypothesis testing by integrating pathway level similarities at the gene level (Little et al. (2023) <doi:10.1111/biom.13769>). The software implements balanced and unbalanced optimal transport and omnibus tests with 'C++' across a set of tumor samples and allows for multi-threading to decrease computational runtime.

Paul Little

ROKET

Optimal Transport-Based Kernel Regression

kOT_sim_OT function

<dl><dt>work_dir</dt>
<dd>A full path to create "sim_ROKET" and subdirectories</dd>
<dt>NN</dt>
<dd>A positive integer for sample size</dd>
<dt>nGENE</dt>
<dd>A positive integer for number of genes to simulate</dd>
<dt>nPATH</dt>
<dd>A positive integer for number of pathways to simulate</dd>
<dt>SCEN</dt>
<dd>An integer taking values 1, 2, 3, or 4</dd>
<dt>ncores</dt>
<dd>A positive integer specifying the number of
cores/threads to use for optimal transport calculations</dd></dl>

Arguments

kOT_sim_OT — kOT_sim_OT

<dl>

<dt>work_dir</dt>
<dd>A full path to create "sim_ROKET" and subdirectories</dd>


<dt>NN</dt>
<dd>A positive integer for sample size</dd>


<dt>nGENE</dt>
<dd>A positive integer for number of genes to simulate</dd>


<dt>nPATH</dt>
<dd>A positive integer for number of pathways to simulate</dd>


<dt>SCEN</dt>
<dd>An integer taking values 1, 2, 3, or 4</dd>


<dt>ncores</dt>
<dd>A positive integer specifying the number of
cores/threads to use for optimal transport calculations</dd>

</dl>

kOT_sim_OT: kOT_sim_OT

Description

Usage

Value

Arguments