qiime feature-table heatmap

Hi everyone, I am using the following commands to mainly look at the dendrogram generated for the samples (to see if my samples cluster together)

qiime feature-table heatmap
–i-table CC_table_lv6.qza
–p-metric braycurtis
–p-cluster samples
–m-sample-metadata-file CC_metadata.txt
–m-sample-metadata-column strain
–o-visualization heatmap/hm_bc_md_strain.qzv

  1. I am assuming --p-metric braycurtis uses the BC metric to cluster my samples. Is there a way to do this using weighted or unweighted uniFrac?
  2. Is there a way to generate or save the dendrogram alone without the heatmap?
  3. A way to control the number of features ( like the top 10, or top50 only)?

I read through the forum and found that I can do 3 using the qiime sample-classifier heatmap - but that requires me running the machine learning.

I would appreciate it if there is any other way to use the distance matrix to create a dendrogram.


Hi @Aravindh_Nagarajan!

No, the metrics in this parameter are from the seaborn tool used to make the plot:

  --p-metric TEXT Choices('mahalanobis', 'chebyshev', 'minkowski',
    'sqeuclidean', 'russellrao', 'sokalmichener', 'dice', 'cityblock',
    'sokalsneath', 'euclidean', 'correlation', 'jaccard', 'cosine',
    'rogerstanimoto', 'hamming', 'braycurtis', 'canberra', 'matching',
    'kulsinski', 'yule', 'seuclidean')
                         Metrics exposed by seaborn (see
                         p.html#seaborn.clustermap for more detail).
                                                        [default: 'euclidean']

Not directly in QIIME 2, but you can export (link) the table and plot in seaborn yourself, or using your favorite tool.

Yes, simply filter the table before plotting it: https://docs.qiime2.org/2020.6/tutorials/filtering/

1 Like

@thermokarst Thank you!

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