An accessible metagenomic strategy allows for better characterization of invertebrate bulk samples

DNA-based techniques are a popular approach for assessing biodiversity in ecological research, especially for organisms that are difficult to detect or identify morphologically. Metabarcoding, the most established method for determining species composition and relative abundance in bulk samples, can be more sensitive and time- and cost-effective than traditional morphological approaches. However, one drawback of this method is PCR bias caused by between-species variation in the amplification efficiency of a marker gene. Metagenomics, bypassing PCR amplification, has been proposed as an alternative to overcome this bias. Several studies have already shown the promising potential of metagenomics, but they all indicate the unavailability of reference genomes for most species in any ecosystem as one of the primary bottlenecks preventing its wider implementation. This dataset is from a study that present a strategy which combines unassembled reads of low-coverage whole genome sequencing and ..., , # An accessible metagenomic strategy allows for better characterization of invertebrate bulk samples

Dataset DOI: [10.5061/dryad.gqnk98szx](10.5061/dryad.gqnk98szx)

## Description of the data and file structure

The Kraken2 custom database was created using unassembled low-coverage genome sequencing data of 24 macrobenthos species from the Belgian part of the North Sea and one publicly available assembled reference genome.

The results from the metagenomic analysis (BIOM file) were obtained by classifying shotgun sequencing reads from environmental macrobenthos bulk samples using our custom database. 

### Files and variables

#### File: macrobenthos\_classification.biom

**Description:** BIOM format v1.0 (see [https://biom-format.org/](https://biom-format.org/) for details) containing the number of metagenomic reads assigned to a particular taxonomic group for each environmental sample. 

#### File: Data\_analysis\_macrobenthos.Rmd

**Description:** R markdown file to perform the sta...,