PRE-PUBLICATION RELEASE: The FADE tool is still under development.
FADE
A FUBAR* Approach to Directional Selection (*Fast, Unconstrained Bayesian AppRoximation for Inferring Selection)
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Standard Error Message
/var/spool/torque/mom_priv/jobs/1920925.new-silverback.SC: line 43: [: Variational-Bayes: integer expression expected
/var/spool/torque/mom_priv/jobs/1920925.new-silverback.SC: line 54: [: missing `]'
Check errors.log for execution error details.
Analysis Description
--------------------
FADE (FUBAR Approach to Directional Evolution) is a fast method to test
whether or not a subset of sites in a protein alignment evolve towards a
particular residue along a subset of branches at accelerated rates
compared to reference model. FADE uses a random effects model and latent
Dirichlet allocation (LDA) - inspired approximation methods to allocate
sites to rate classes.
- __Requirements__: A protein alignment and a **rooted** phylogenetic tree (optionally
annotated with {})
- __Citation__: TBD
- __Written by__: Sergei L Kosakovsky Pond
- __Contact Information__: spond@temple.edu
- __Analysis Version__: 0.2
Save FADE cache to :
>cache –> /home/datamonkey/datamonkey-js-server/production/app/fade/output/61eec4295e56f71949c04edd.FADE.cache
> FADE will write cache and result files to _/home/datamonkey/datamonkey-js-server/production/app/fade/output/61eec4295e56f71949c04edd.FADE.cache_ and _/home/datamonkey/datamonkey-js-server/production/app/fade/output/61eec4295e56f71949c04edd.FADE.json_, respectively
### Loaded **59** sequences, **3231** sites, and **1** partitions from `/home/datamonkey/datamonkey-js-server/production/app/fade/output/61eec4295e56f71949c04edd`
Error:
Input tree MUST be rooted in call to assert(((fade.partitions_and_trees[index])[terms.data.tree])[terms.trees.rooted], "Input tree MUST be rooted");
Function call stack
1 : assert(((fade.partitions_and_trees[index])[terms.data.tree])[terms.trees.rooted], "Input tree MUST be rooted");
Keyword arguments:
{
"branches":"All",
"burn-in":"1000000",
"chain":"5",
"chains":"2000000",
"concentration_parameter":"0.5",
"grid":"20",
"method":"Variational-Bayes",
"model":"LG",
"samples":"100",
"tree":"/home/datamonkey/datamonkey-js-server/production/app/fade/output/61eec4295e56f71949c04edd.tre"
}
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