qiime feature-table heatmap

[Aravindh_Nagarajan]

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.

Thanks!

[thermokarst]

Hi @Aravindh_Nagarajan!

@Aravindh_Nagarajan

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?

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
                         http://seaborn.pydata.org/generated/seaborn.clusterma
                         p.html#seaborn.clustermap for more detail).
                                                        [default: 'euclidean']

@Aravindh_Nagarajan

Is there a way to generate or save the dendrogram alone without the heatmap?

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

@Aravindh_Nagarajan

A way to control the number of features ( like the top 10, or top50 only)?

Yes, simply filter the table before plotting it: Filtering data — QIIME 2 2020.6.0 documentation

[Aravindh_Nagarajan]

@thermokarst Thank you!