subset_by_col_and_filt

Subset table by set of column names. After doing this, it will remove any rows and columns that are all 0's.

Code to identify functional enrichments across diverse taxa
in phylogenetic tree, particularly where these taxa differ in
abundance across samples in a non-random pattern. The motivation for
this approach is to identify microbial functions encoded by diverse
taxa that are at higher abundance in certain samples compared to
others, which could indicate that such functions are broadly adaptive
under certain conditions. See 'GitHub' repository for tutorial and
examples: <https://github.com/gavinmdouglas/POMS/wiki>. Citation: Gavin M. Douglas, Molly G. Hayes, Morgan G. I. Langille, Elhanan Borenstein (2022) <doi:10.1093/bioinformatics/btac655>.

Gavin Douglas

POMS

Phylogenetic Organization of Metagenomic Signals

subset_by_col_and_filt function

<dl><dt>in_tab</dt>
<dd>input dataframe</dd>
<dt>col2keep</dt>
<dd>column names to retain in output (as long as they have at least one non-zero value).</dd>
<dt>verbose</dt>
<dd>flag to indicate that the final number of rows and columns (as well as the number removed) should be reported.</dd></dl>

Arguments

Subset dataframe by column names and then post-filter — subset_by_col_and_filt

<dl>

<dt>in_tab</dt>
<dd>input dataframe</dd>


<dt>col2keep</dt>
<dd>column names to retain in output (as long as they have at least one non-zero value).</dd>


<dt>verbose</dt>
<dd>flag to indicate that the final number of rows and columns (as well as the number removed) should be reported.</dd>

</dl>

subset_by_col_and_filt: Subset dataframe by column names and then post-filter

Description

Usage

Value

Arguments