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To directly measure the robustness of individual UPGMA clusters and clusters in PCoA plots, one can perform jackknifing (repeatedly resampling a subset of the available data from each sample).
Usage: jackknifed_beta_diversity.py [options]
This scripts results in several distance matrices (from beta_diversity.py), several rarefied OTU tables (from multiple_rarefactions_even_depth.py), several UPGMA trees (from upgma_cluster.py), a supporting file and newick tree with support values (from tree_compare.py), and Emperor PCoA plots.
These steps are performed by the following command: Compute beta diversity distance matrix from otu table (and tree, if applicable); build rarefied OTU tables by evenly sampling to the specified depth (-e); build UPGMA tree from full distance matrix; compute distance matrics for rarefied OTU tables; build UPGMA trees from rarefied OTU table distance matrices; build a consensus tree from the rarefied UPGMA trees; compare rarefied OTU table distance matrix UPGMA trees to either (full or consensus) tree for jackknife support of tree nodes; perform principal coordinates analysis on distance matrices generated from rarefied OTU tables; generate Emperor PCoA plots with jackknifed support.
jackknifed_beta_diversity.py -i otu_table.biom -o bdiv_jk100 -e 100 -m Fasting_Map.txt -t rep_set.tre