recipe metaclassifier

MetaClassifier is an integrated pipeline for classifying and quantifying DNA metabarcoding data into taxonomy groups



GPL3 / GNU General Public v3 (GPLv3)



MetaClassifier is an integrated pipeline for identifying the floral composition of honey using DNA metabarcoding to determine the plants that honey bees visit. MetaClassifier utilizes a database of marker sequences and their corresponding taxonomy lineage information to classify high-throughput metabarcoding sample sequencing reads data into taxonomic groups and quantify taxon abundance. MetaClassifier can also be employed in other studies that utilize barcoding, metabarcoding, and metagenomics techniques to characterize richness, abundance, relatedness, and interactions in ecological communities.

package metaclassifier

(downloads) docker_metaclassifier



depends numpy:


depends pandas:


depends pear:


depends python:


depends seqtk:


depends vsearch:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install metaclassifier

and update with::

   mamba update metaclassifier

To create a new environment, run:

mamba create --name myenvname metaclassifier

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `metaclassifier/tags`_ for valid values for ``<tag>``)

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