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add 'cluster' and 'cocluster' to sourmash #700
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see also #1265, uniqify script, which I think is nice and simple. |
may be good as a plugin test #1353 |
This was referenced Mar 4, 2021
bluegenes
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Feb 27, 2024
This PR adds a new command, `cluster`, that can be used to cluster the output from `pairwise` and `multisearch`. `cluster`uses `rustworkx-core` (which internally uses `petgraph`) to build a graph, adding edges between nodes when the similarity exceeds the user-defined threshold. It can work on any of the similarity columns output by `pairwise` or `multisearch`, and will add all nodes to the graph to preserve singleton 'clusters' in the output. `cluster` outputs two files: 1. cluster identities file: `Component_X, name1;name2;name3...` 2. cluster size histogram `cluster_size, count` context for some things I tried: - try using petgraph directly and removing rustworkx dependency > nope,`rustworkx-core` adds `connected_components` that returns the connected components, rather than just the number of connected components. Could reimplement if `rustworkx-core` brings in a lot of deps - try using 'extend_with_edges' instead of add_edge logic. > nope, only in `petgraph` **Punted Issues:** - develop clustering visualizations (ref @mr-eyes kSpider/dbretina work). Optionally output dot file of graph? (#248) - enable updating clusters, rather than always regenerating from scratch (#249) - benchmark `cluster` (#247) > `pairwise` files can be millions of lines long. Would it be faster to parallel read them, store them in an `edges` vector, and then add nodes/edges sequentially? Note that we would probably need to either 1. store all edges, including those that do not pass threshold) or 2. After building the graph from edges, add nodes from `names_to_node` that are not already in the graph to preserve singletons. Related issues: * #219 * sourmash-bio/sourmash#2271 * sourmash-bio/sourmash#700 * sourmash-bio/sourmash#225 * sourmash-bio/sourmash#274 --------- Co-authored-by: C. Titus Brown <[email protected]>
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the cocluster script may be useful for people comparing the output of binning.
see also #459
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