Microbiome abundances (60 taxa and 155 individuals) from an HIV study (Noguera-Julian et al. 2016).

data

Functions for microbiome data analysis that take into account its compositional nature. Performs variable selection through penalized regression for both, cross-sectional and longitudinal studies, and for binary and continuous outcomes.

Toni Susin

coda4microbiome

Compositional Data Analysis for Microbiome Studies

Malu Calle

Meritxell Pujolassos

HIV function

The dataset contains three objects:<dl>
<dt>x_HIV</dt>
<dd>microbiome abundance matrix for 155 individuals (rows) and 60 genera (columns)</dd><dt>y_HIV</dt>
<dd>a factor, specifying if the individual is HIV positive or (<code>Pos</code>) or negative (<code>Neg</code>).</dd><dt>MSM_HIV</dt>
<dd>a factor, indicating sexual preferences: <code>MSM</code> (Men who have Sex with Men) or not (<code>nonMSM</code>).</dd>
</dl>

Format

HIV — HIV

The dataset contains three objects:<dl>
<dt>x_HIV</dt>
<dd>microbiome abundance matrix for 155 individuals (rows) and 60 genera (columns)</dd>

<dt>y_HIV</dt>
<dd>a factor, specifying if the individual is HIV positive or (<code>Pos</code>) or negative (<code>Neg</code>).</dd>

<dt>MSM_HIV</dt>
<dd>a factor, indicating sexual preferences: <code>MSM</code> (Men who have Sex with Men) or not (<code>nonMSM</code>).</dd>


</dl>

HIV: HIV

Description

Arguments

Format

References