Mercurial > repos > iuc > hyphy_absrel

diff test-data/summary/nsp8.combined.fas.BGM.json @ 27:8633ea985719 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/hyphy/ commit 00684bab4c9e740cfa6a39abc444380e6818fd97"
author iuc
date Wed, 09 Jun 2021 07:04:45 +0000
parents
children
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/summary/nsp8.combined.fas.BGM.json	Wed Jun 09 07:04:45 2021 +0000
@@ -0,0 +1,253 @@
+{
+ "analysis":{
+   "authors":"Art FY Poon, Fraser I Lewis, Simon DW Frost and Sergei L Kosakovsky Pond",
+   "citation":"Spidermonkey: rapid detection of co-evolving sites using Bayesian graphical models (2008). _Bioinformatics_ 24(17): 1949-1950",
+   "contact":"apoon42@uwo.ca",
+   "info":"BGM (Bayesian Graphical Model) uses a maximum likelihood ancestral state reconstruction to\nmap substitution (non-synonymous only for coding data) events to branches in the\nphylogeny and then analyzes the joint distribution of the\nsubstitution map using a Bayesian graphical model (network).\nNext, a Markov chain Monte Carlo analysis is used to generate\na random sample of network structures from the posterior\ndistribution given the data.  Each node in the network\nrepresents a codon site in the alignment, and links (edges)\nbetween nodes indicate high posterior support for correlated\nsubstitutions at the two sites over time, which implies coevolution.",
+   "requirements":"in-frame codon alignment and a phylogenetic tree",
+   "version":"1.2"
+  },
+ "branch attributes":{
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+ "data partitions":{
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+      ],
+     "name":"bgm.filter.default"
+    }
+  },
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+     "Log Likelihood":-1205.948282908683,
+     "Rate Distributions":null,
+     "display order":0,
+     "estimated parameters":76
+    }
+  },
+ "input":{
+   "datatype":"codon",
+   "file name":"/home/aglucaci/SARS-CoV-2/clades/B-1-617/nsp8.combined.fas",
+   "number of sequences":32,
+   "number of sites":198,
+   "trees":{
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+    }
+  },
+ "settings":{
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+   "data-type":"codon",
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+   "min-subs":1,
+   "samples":100,
+   "steps":100000,
+   "threshold":0.5
+  },
+ "tested":0,
+ "timers":{
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+     "order":1,
+     "timer":4
+    },
+   "Network inference":{
+     "order":2,
+     "timer":0
+    },
+   "Overall":{
+     "order":0,
+     "timer":4
+    }
+  }
+}
\ No newline at end of file