training.ASV.table

Placeholder description for training.ASV.table dataset.

datasets

A series of R functions that come in handy while working with metabarcoding data.
The reasoning of doing this is to have the same functions we use all the time stored in a curated, reproducible way.
In a way it is all about putting together the grammar of the 'tidyverse' from Wickham et al.(2019) <doi:10.21105/joss.01686>
with the functions we have used in community ecology compiled in packages like 'vegan' from Dixon (2003) <doi:10.1111/j.1654-1103.2003.tb02228.x>
and 'phyloseq' McMurdie & Holmes (2013) <doi:10.1371/journal.pone.0061217>.
The package includes functions to read sequences from FAST(A/Q) into a tibble ('fasta_reader' and 'fastq_reader'),
to process 'cutadapt' Martin (2011) <doi:10.14806/ej.17.1.200> 'info-file' output. When it comes to sequence counts across samples, the package
works with the long format in mind (a three column 'tibble' with Sample, Sequence and counts ), with functions to move from there to the wider format.

Ramón Gallego Simón

eDNAfuns

Working with Metabarcoding Data in a Tidy Format

training.ASV.table function

A data frame with 1909 rows and 4 variables:<dl>
 <dt>Sample_name</dt>
<dd>Character vector, last digit includes PCR replicate</dd> <dt>Locus</dt>
<dd>Which locus the sequences are from, numeric</dd> <dt>Hash</dt>
<dd>The sequence found, hashed using sha1 for consistency</dd> <dt>nReads</dt>
<dd>Number of times that hash was found in that sample</dd>
</dl>

Format

training.ASV.table — training.ASV.table

A data frame with 1909 rows and 4 variables:<dl>
 <dt>Sample_name</dt>
<dd>Character vector, last digit includes PCR replicate</dd>

 <dt>Locus</dt>
<dd>Which locus the sequences are from, numeric</dd>

 <dt>Hash</dt>
<dd>The sequence found, hashed using sha1 for consistency</dd>

 <dt>nReads</dt>
<dd>Number of times that hash was found in that sample</dd>


</dl>

training.ASV.table: training.ASV.table

Description

Usage

Arguments

Format