PlotPathInner

Visualisation Original features that make up the pathway

Biologically Explainable Machine Learning Framework for Phenotype Prediction using omics data described in Chen and Schwarz (2017) <doi:10.48550/arXiv.1712.00336>.Identifying reproducible and interpretable biological patterns from high-dimensional omics data is a critical factor in understanding the risk mechanism of complex disease. As such, explainable machine learning can offer biological insight in addition to personalized risk scoring.In this process, a feature space of biological pathways will be generated, and the feature space can also be subsequently analyzed using WGCNA (Described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559> ) methods.

Shunjie Zhang

BioM2

Biologically Explainable Machine Learning Framework

Junfang Chen

PlotPathInner function

<dl><dt>data</dt>
<dd>The input omics data</dd>
<dt>pathlistDB</dt>
<dd>A list of pathways with pathway IDs and their corresponding genes ('entrezID' is used).
For details, please refer to ( data("GO2ALLEGS_BP") )</dd>
<dt>FeatureAnno</dt>
<dd>The annotation data stored in a data.frame for probe mapping.
It must have at least two columns named 'ID' and 'entrezID'.
(For details, please refer to data( data("MethylAnno") )</dd>
<dt>PathNames</dt>
<dd>A vector.A vector containing the names of pathways</dd>
<dt>p.adjust.method</dt>
<dd>p-value adjustment method.(holm", "hochberg", "hommel",
"bonferroni", "BH", "BY","fdr","none")</dd>
<dt>save_pdf</dt>
<dd>Whether to save images in PDF format</dd>
<dt>alpha</dt>
<dd>The alpha transparency, a number in (0,1).</dd>
<dt>cols</dt>
<dd>palette (vector of colour names)</dd></dl>

Arguments

Visualisation Original features that make up the pathway — PlotPathInner

<dl>

<dt>data</dt>
<dd>The input omics data</dd>


<dt>pathlistDB</dt>
<dd>A list of pathways with pathway IDs and their corresponding genes ('entrezID' is used).
For details, please refer to ( data("GO2ALLEGS_BP") )</dd>


<dt>FeatureAnno</dt>
<dd>The annotation data stored in a data.frame for probe mapping.
It must have at least two columns named 'ID' and 'entrezID'.
(For details, please refer to data( data("MethylAnno") )</dd>


<dt>PathNames</dt>
<dd>A vector.A vector containing the names of pathways</dd>


<dt>p.adjust.method</dt>
<dd>p-value adjustment method.(holm", "hochberg", "hommel",
"bonferroni", "BH", "BY","fdr","none")</dd>


<dt>save_pdf</dt>
<dd>Whether to save images in PDF format</dd>


<dt>alpha</dt>
<dd>The alpha transparency, a number in (0,1).</dd>


<dt>cols</dt>
<dd>palette (vector of colour names)</dd>

</dl>

PlotPathInner: Visualisation Original features that make up the pathway

Description

Usage

Value

Arguments