nice_env

This dataset provides information on the samples used for the N-ICE dataset.

datasets

A tool to define rare biosphere. 'ulrb' solves the problem of the
definition of rarity by replacing arbitrary thresholds with an unsupervised machine
learning algorithm (partitioning around medoids, or k-medoids). This algorithm
works for any type of microbiome data, provided there is an abundance table.
For validation of this method to different abundance tables, see Pascoal et al, 2025.
This method also works for non-microbiome data.

Francisco Pascoal

ulrb

Unsupervised Learning Based Definition of Microbial Rare
Biosphere

Paula Branco

Luís Torgo

Rodrigo Costa

Catarina Magalhães

nice_env function

<div class="section" id="nice-tidy">
<h3><code>nice_tidy</code></h3>
A data frame with 4716 rows and 10 columns:<dl>
<dt>Sample</dt>
<dd>Sample ID used in the original study</dd><dt>ENA_ID</dt>
<dd>Sample ID equivalent to Sample in the OTU table</dd><dt>Month</dt>
<dd>Month of sampling</dd><dt>Region</dt>
<dd>Ocean region of sampling event</dd><dt>Water.mass</dt>
<dd>Water mass of sampling event</dd><dt>Latitude</dt>
<dd>Latitude of sampling event</dd><dt>Longitude</dt>
<dd>Longitude of sampling event</dd></dl></div>

Format

Metadata of samples from OTU tables (N-ICE, 2015) — nice_env

<div class='section' id='nice-tidy'>
<h3><code>nice_tidy</code></h3>


A data frame with 4716 rows and 10 columns:<dl>
<dt>Sample</dt>
<dd>Sample ID used in the original study</dd>

<dt>ENA_ID</dt>
<dd>Sample ID equivalent to Sample in the OTU table</dd>

<dt>Month</dt>
<dd>Month of sampling</dd>

<dt>Region</dt>
<dd>Ocean region of sampling event</dd>

<dt>Water.mass</dt>
<dd>Water mass of sampling event</dd>

<dt>Latitude</dt>
<dd>Latitude of sampling event</dd>

<dt>Longitude</dt>
<dd>Longitude of sampling event</dd>



</dl>

</div>

nice_env: Metadata of samples from OTU tables (N-ICE, 2015)

Description

Usage

Arguments

Format

`nice_tidy`

Details

References

See Also