Difference between revisions of "Applications/BayesTraits"

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* Version: 3.0.0 (supplied compiled binaries)
 
* Version: 3.0.0 (supplied compiled binaries)
 
* Modules: bayes/3.0.0 (apps)
 
* Modules: bayes/3.0.0 (apps)
* Licence: Free (http://www.evolution.rdg.ac.uk/index.html)
+
* Licence: Free  
 +
 
 +
==Introduction==
 +
 
 +
BayesTraits is a computer package for performing analyses of trait evolution among groups of species for which a phylogeny or sample of phylogenies is available.  
 +
 
 +
This new package incorporates our earlier and separate programs Multistate, Discrete and Continuous.  
 +
 
 +
BayesTraits can be applied to analysing traits that adopt a finite number of discrete states, or to analysing continuously varying traits. Hypotheses can be tested about models of evolution, ancestral states and correlations among pairs of traits.
  
 
==Usage Examples==
 
==Usage Examples==
  
===Interactive Session===
+
===Interactive Session===
  
 
<pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
<pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
Line 17: Line 25:
 
salloc: Granted job allocation 409670
 
salloc: Granted job allocation 409670
 
Job ID 409670 connecting to c128, please wait...
 
Job ID 409670 connecting to c128, please wait...
[username@c128 ~]$ module load bayesTrait/3.0.0
+
[username@c128 ~]$ module add bayesTrait/3.0.0
 
[username@c128 ~]$ BayesTraitsV3 /trinity/clustervision/CentOS/7/apps/bayesTraits/3.0.0/Mammal.trees bob.tress
 
[username@c128 ~]$ BayesTraitsV3 /trinity/clustervision/CentOS/7/apps/bayesTraits/3.0.0/Mammal.trees bob.tress
 
BayesTraits V3.0 (Mar  2 2017)
 
BayesTraits V3.0 (Mar  2 2017)
 
Mark Pagel and Andrew Meade
 
Mark Pagel and Andrew Meade
 
www.evolution.reading.ac.uk
 
www.evolution.reading.ac.uk
...
 
  
 
</pre>
 
</pre>
  
===Batch Session===
+
===Batch Session===
 +
 
 +
<pre style="background-color: #E5E4E2; color: black; font-family: monospace, sans-serif;">
 +
#!/bin/bash
 +
 
 +
#SBATCH -J BayesTrait # Job Name
 +
#SBATCH -N 1      # Number of  Nodes to use
 +
#SBATCH  -n 28  # Number of CPUs
 +
#SBATCH -o %N.%j.%a.out # Output file name
 +
#SBATCH -e %N.%j.%a.err  # Error file name
 +
#SBATCH -p compute      # Partition to run on
 +
#SBATCH --exclusive      # Instructs SLURM to not run any other job in the node(s) selected
 +
#SBATCH --mail-user= your email address here
 +
 
 +
module add bayesTraits/3.0.0
 +
BayesTraitsV3 Mammal.trees bob.tress < command.txt
 +
 
 +
</pre>
  
 
<pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
<pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
Line 35: Line 59:
 
</pre>
 
</pre>
  
 +
===Multi-Batch Jobs===
  
==Further Information==
+
The following job script will automatically run 3 identical BayesTrait jobs in an array so that three outputs can be compared. It takes care of separating the jobs, running them, and then bringing the outputs together.
 +
 
 +
<pre style="background-color: #E5E4E2; color: black; font-family: monospace, sans-serif;">
 +
#!/bin/bash
 +
#SBATCH -J BayesTrait_array
 +
#SBATCH -N 1
 +
#SBATCH  -n 28
 +
#SBATCH -o %N.%j.%a.out
 +
#SBATCH -e %N.%j.%a.err
 +
#SBATCH -pcompute
 +
#SBATCH --exclusive
 +
#SBATCH --array 1-3
 +
 +
module add bayesTraits/3.0/intel-2017
 +
 +
# Create 3 sub-directories inside which each job will run
 +
RUNDIR=`pwd`
 +
mkdir $SLURM_ARRAY_TASK_ID
 +
cd $SLURM_ARRAY_TASK_ID
 +
 +
# Update here to set command, tree, and data files
 +
COMMAND_FILE=MCcSM_RJHPexp05_WCLCBNoZero_command.txt
 +
TREE_FILE=FritzHARD_WCLCBNoZero.trees
 +
DATA_FILE=MCcSM_RJHPexp05_WCLCBNoZero.txt
 +
 
 +
# Make a 'copy' of the command, tree and data files in the job sub-directories
 +
ln -s ../$COMMAND_FILE .
 +
ln -s ../$TREE_FILE .
 +
ln -s ../$DATA_FILE .
 +
 +
BayesTraitsV3 $TREE_FILE $DATA_FILE < $COMMAND_FILE
 +
 +
cd $RUNDIR
 +
 +
# Copy the output files from each of the 3 run directories into a file called run_1_<data_file>.log.txt
 +
cp $SLURM_ARRAY_TASK_ID/${DATA_FILE}.Log.txt run_${SLURM_ARRAY_TASK_ID}_${DATA_FILE}.Log.txt
 +
cp $SLURM_ARRAY_TASK_ID/${DATA_FILE}.Schedule.txt run_${SLURM_ARRAY_TASK_ID}_${DATA_FILE}.Schedule.txt
 +
</pre>
 +
 
 +
<pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 +
 
 +
[user@login01 ~]$ sbatch bayestrait-multi-test.job
 +
Submitted batch job 409681
 +
 
 +
</pre>
  
* [http://http://www.evolution.rdg.ac.uk/index.html http://www.evolution.rdg.ac.uk/index.html]
 
  
 +
==Next Steps==
  
 +
* [http://http://www.evolution.rdg.ac.uk/index.html http://www.evolution.rdg.ac.uk/index.html]
  
{|
+
{{Modulepagenav}}
|style="width:5%; border-width: 0" | [[File:icon_home.png]]
 
|style="width:95%; border-width: 0" |
 
* [[Main_Page|Home]]
 
* [[Applications|Application support]]
 
* [[General|General]]
 
* [[Training|Training]]
 
* [[Programming|Programming support]]
 
|-
 
|}
 

Latest revision as of 09:49, 23 March 2023

Application Details

  • Description: BayesTraits
  • Version: 3.0.0 (supplied compiled binaries)
  • Modules: bayes/3.0.0 (apps)
  • Licence: Free

Introduction

BayesTraits is a computer package for performing analyses of trait evolution among groups of species for which a phylogeny or sample of phylogenies is available.

This new package incorporates our earlier and separate programs Multistate, Discrete and Continuous.

BayesTraits can be applied to analysing traits that adopt a finite number of discrete states, or to analysing continuously varying traits. Hypotheses can be tested about models of evolution, ancestral states and correlations among pairs of traits.

Usage Examples

Interactive Session


[user@login01 ~]$ interactive
salloc: Granted job allocation 409670
Job ID 409670 connecting to c128, please wait...
[username@c128 ~]$ module add bayesTrait/3.0.0
[username@c128 ~]$ BayesTraitsV3 /trinity/clustervision/CentOS/7/apps/bayesTraits/3.0.0/Mammal.trees bob.tress
BayesTraits V3.0 (Mar  2 2017)
Mark Pagel and Andrew Meade
www.evolution.reading.ac.uk

Batch Session

#!/bin/bash

#SBATCH -J BayesTrait # Job Name
#SBATCH -N 1      # Number of  Nodes to use
#SBATCH  -n 28   # Number of CPUs
#SBATCH -o %N.%j.%a.out # Output file name
#SBATCH -e %N.%j.%a.err  # Error file name
#SBATCH -p compute       # Partition to run on
#SBATCH --exclusive       # Instructs SLURM to not run any other job in the node(s) selected
#SBATCH --mail-user= your email address here

module add bayesTraits/3.0.0
BayesTraitsV3 Mammal.trees bob.tress < command.txt


[user@login01 ~]$ sbatch bayestrait-test.job
Submitted batch job 409671

Multi-Batch Jobs

The following job script will automatically run 3 identical BayesTrait jobs in an array so that three outputs can be compared. It takes care of separating the jobs, running them, and then bringing the outputs together.

#!/bin/bash
#SBATCH -J BayesTrait_array
#SBATCH -N 1
#SBATCH  -n 28
#SBATCH -o %N.%j.%a.out
#SBATCH -e %N.%j.%a.err
#SBATCH -pcompute
#SBATCH --exclusive
#SBATCH --array 1-3
 
module add bayesTraits/3.0/intel-2017
 
# Create 3 sub-directories inside which each job will run
RUNDIR=`pwd`
mkdir $SLURM_ARRAY_TASK_ID
cd $SLURM_ARRAY_TASK_ID
 
# Update here to set command, tree, and data files 
COMMAND_FILE=MCcSM_RJHPexp05_WCLCBNoZero_command.txt
TREE_FILE=FritzHARD_WCLCBNoZero.trees
DATA_FILE=MCcSM_RJHPexp05_WCLCBNoZero.txt

# Make a 'copy' of the command, tree and data files in the job sub-directories
ln -s ../$COMMAND_FILE .
ln -s ../$TREE_FILE .
ln -s ../$DATA_FILE .
 
BayesTraitsV3 $TREE_FILE $DATA_FILE < $COMMAND_FILE
 
cd $RUNDIR
 
# Copy the output files from each of the 3 run directories into a file called run_1_<data_file>.log.txt
cp $SLURM_ARRAY_TASK_ID/${DATA_FILE}.Log.txt run_${SLURM_ARRAY_TASK_ID}_${DATA_FILE}.Log.txt
cp $SLURM_ARRAY_TASK_ID/${DATA_FILE}.Schedule.txt run_${SLURM_ARRAY_TASK_ID}_${DATA_FILE}.Schedule.txt

[user@login01 ~]$ sbatch bayestrait-multi-test.job
Submitted batch job 409681


Next Steps





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