Galaxy | Tool Preview

qiime2 vsearch cluster-features-de-novo (version 2023.5.0+q2galaxy.2023.5.0.2)
[required] The sequences corresponding to the features in table.
[required] The feature table to be clustered.
[required] The percent identity at which clustering should be performed. This parameter maps to vsearch's --id parameter.
Click here for additional options
Click here for additional options 0

QIIME 2: vsearch cluster-features-de-novo

De novo clustering of features.

Outputs:

clustered_table.qza:
 The table following clustering of features.
clustered_sequences.qza:
 Sequences representing clustered features.

Description:

Given a feature table and the associated feature sequences, cluster the features based on user-specified percent identity threshold of their sequences. This is not a general-purpose de novo clustering method, but rather is intended to be used for clustering the results of quality-filtering/dereplication methods, such as DADA2, or for re-clustering a FeatureTable at a lower percent identity than it was originally clustered at. When a group of features in the input table are clustered into a single feature, the frequency of that single feature in a given sample is the sum of the frequencies of the features that were clustered in that sample. Feature identifiers and sequences will be inherited from the centroid feature of each cluster. See the vsearch documentation for details on how sequence clustering is performed.