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This script visualizes an OTU table as a heatmap where each row corresponds to an OTU and each column corresponds to a sample. The higher the relative abundance of an OTU in a sample, the more intense the color at the corresponsing position in the heatmap. By default, the OTUs (rows) will be clustered by UPGMA hierarchical clustering, and the samples (columns) will be presented in the order in which they appear in the OTU table. Alternatively, the user may supply a tree to sort the OTUs (rows) or samples (columns), or both. The user may also pass in a mapping file for sorting samples. If the user passes in a mapping file and a metadata category, samples (columns) will be grouped by category value and subsequently clustered within each group.
Usage: make_otu_heatmap.py [options]
A single output file is created containing the heatmap of the OTU table (a PDF file by default).
Generate a heatmap as a PDF using all default values:
make_otu_heatmap.py -i otu_table.biom -o heatmap.pdf
Generate a heatmap as a PNG:
make_otu_heatmap.py -i otu_table.biom -o heatmap.png -g png
Sort the heatmap columns (samples) by the order of samples in the mapping file
make_otu_heatmap.py -i otu_table.biom -o heatmap_sorted_samples.pdf -m mapping_file.txt
Sort the heatmap columns (samples) by the order of samples in the mapping file, and sort the heatmap rows by the order of tips in the tree:
make_otu_heatmap.py -i otu_table.biom -o heatmap_sorted.pdf -m mapping_file.txt -t rep_set.tre
Group the heatmap columns (samples) by metadata category (e.g., Treatment), then cluster within each group:
make_otu_heatmap.py -i otu_table.biom -o heatmap_grouped_by_Treatment.pdf -m mapping_file.txt -c Treatment