jrober84 / mobclustering

Benchmarking methods for plasmid clustering

mobclustering

Benchmarking methods for plasmid clustering

#identifying smallest mash distance from report python find_smallest_dist.py -i mash_dist_file.txt

converting fastANI results to distance matrix

python process_ani_results_to_matrix.py -i fastANI_distances.txt -o fastANI.matrix.txt

Determine cluster metrics for mash based clusters

python replicon_relaxase_concordance_clusters_mash.py

-- accepts on of the 2019-12-10-mash-clustering-* files and outputs the following fields threshold level mean shannon entropy stdev shannon entropy mean cluster sizes stdev cluster sizes mean number of types within a cluster stdev number of types within a cluster

Determine cluster metrics for ani based clusters

python replicon_relaxase_concordance_clusters_mash.py

-- accepts on of the 2019-12-10-ani-clustering-* files and outputs the following fields threshold level mean shannon entropy stdev shannon entropy mean cluster sizes stdev cluster sizes mean number of types within a cluster stdev number of types within a cluster

taxonomy convergence analysis

python taxonomy_convergence.py

-- Uses the Taxonomy_NCBI_Plasmids.txt file to output the following fields based on the taxa associated with each feature accession overall_convergence_rank overall_convergence_name convergence_rank_replicon convergence_name_replicon convergence_rank_relaxase convergence_name_relaxase convergence_rank_mobcluster convergence_name_mobcluster