Mercurial > repos > iuc > hyphy_strike_ambigs
comparison test-data/summary/nsp8.combined.fas.BGM.json @ 3:204ac950894d draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/hyphy/ commit 00684bab4c9e740cfa6a39abc444380e6818fd97"
author | iuc |
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date | Wed, 09 Jun 2021 07:10:18 +0000 |
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1 { | |
2 "analysis":{ | |
3 "authors":"Art FY Poon, Fraser I Lewis, Simon DW Frost and Sergei L Kosakovsky Pond", | |
4 "citation":"Spidermonkey: rapid detection of co-evolving sites using Bayesian graphical models (2008). _Bioinformatics_ 24(17): 1949-1950", | |
5 "contact":"apoon42@uwo.ca", | |
6 "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.", | |
7 "requirements":"in-frame codon alignment and a phylogenetic tree", | |
8 "version":"1.2" | |
9 }, | |
10 "branch attributes":{ | |
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202 }, | |
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207 ], | |
208 "name":"bgm.filter.default" | |
209 } | |
210 }, | |
211 "fits":{ | |
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214 "Log Likelihood":-1205.948282908683, | |
215 "Rate Distributions":null, | |
216 "display order":0, | |
217 "estimated parameters":76 | |
218 } | |
219 }, | |
220 "input":{ | |
221 "datatype":"codon", | |
222 "file name":"/home/aglucaci/SARS-CoV-2/clades/B-1-617/nsp8.combined.fas", | |
223 "number of sequences":32, | |
224 "number of sites":198, | |
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227 } | |
228 }, | |
229 "settings":{ | |
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231 "data-type":"codon", | |
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234 "samples":100, | |
235 "steps":100000, | |
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237 }, | |
238 "tested":0, | |
239 "timers":{ | |
240 "Baseline fit":{ | |
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243 }, | |
244 "Network inference":{ | |
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247 }, | |
248 "Overall":{ | |
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251 } | |
252 } | |
253 } |