Bayesian_PhylogenetiMSA_fasta00 >ABY27676/1-453 ABY27676 ------------------------------------------------------------------------ ------------------------------------------------------------------------ ------------------------------------------------------------TTAATATTAGGA GCTCCAGATATAGCTTTTCCTCGAATAAATAATCTTAGTTTTTGGTTGCTTCCTCCTTCTTTGATTTTATTA ATAATTTCTTCAATAGTGGAGATAGGGGTTGGGGCGGGGTGAACTATTTATCCTCCTTTATCGGGTAGTCTA GGTCATTCAGGGGTTTCAGTAGATTTAGCTATTTTTAGCTTACATTTGGCGGGAGCTTCTTCAATTATAGGA GCAATTAATTTTATTTCCACTATTTTAAATATACGTTCAGTTGGGATATCTATAGATAAGGTACCTTTATTT GTGTGATCTGTATTAGTTACTGCTGTTTTATTATTATTATCTTTACCAGTTTTAGCCTGGGGTATTACGATA TTATTAACAGATCGAAATTTTAACACTTCTTTTTTTGACCCTGCGGGTGGAGGTGATCCAATTTTATTTCAA CATCTTTTT >ADW61587/1-657 ADW61587 ACGTTATATTTAATATTTGGGGCTTGAGCTGCTATAGTAGGAACAGCCATAAGAGTATTAATTCGAATTGAA TTAGGTCAACCTGGGAGGTTTATTGGGGATGATCAATTATATAATGTAATCGTTACTGCTCATGCATTTGTT ATAATTTTTTTTATAGTAATACCTATTTTGATTGGAGGATTTGGAAATTGATTAGTTCCTTTAATATTAGGC GCTCCTGATATAGCTTTTCCTCGTATAAATAATTTAAGATTTTGGCTACTCCCTCCTTCATTATTTTTATTA ATTATTTCTTCTATAGTAGAAATGGGAGTGGGGGCAGGATGGACGGTTTATCCTCCTTTAGCTAGTTTAGAG GGCCATGCTGGCAGGTCAGTGGATTTTGCTATTTTTTCTTTACATTTAGCGGGGGCCTCCTCTATTATGGGG GCTATTAATTTTATTTCTACTATTATTAATATACGATCGCATGGAATAACTATAGAAAAAGTACCTTTATTT GTATGATCAGTATTGATTACTGCTGTATTATTATTATTATCACTTCCAGTATTGGCGGGGGCTATCACAATA TTATTAACTGATCGAAATTTTAATACTTCGTTTTTTGACCCTTCAGGAGGGGGGGATCCAATCCTTTTCCAA CATTTATTT >AEE92862/1-657 AEE92862 ACGTTATATTTTGTTTTTGGAGCTTGATCTGCTATGGTAGGGACCGGAATAAGAGTAATTATTCGGTCTGAG TTGGGGCAAGTGGGGAGATTGTTGGGTGATGATCATATATATAATGTTATGGTAACTGCTCATGCTTTAGTA ATGATTTTTTTTATGGTAATGCCAATCATGATTGGAGGTTTTGGTAATTGATTACTGCCTTTAATAGTAGGA GCTCCTGATATGGCTTTTCCTCGTATAAATAATTTGAGTTTTTGATTGCTTCCACCTTCTTTATTTTTGTTG GTGTTGTCTTCTTTAACAGATGTTGGGGTAGGGGCTGGTTGAACTATTTATCCTCCTTTGTCTTCGGGAGTT GGGCATGGAGGTGGGGGTATGGATTTTGCTATTTTTTCTTTGCATTTAGCTGGGGCTTCTTCTATTATGGGG GCGATTAATTTTATTACCACTATTATTAATATGCGTACAAATGGTATAACTATGGAGCGTGTGCCGTTGTTT GTGTGATCAGTATTAGTGACTGCTATTTTGTTATTATTGTCTTTACCAGTATTGGCGGGGGCTATTACGATA TTACTAACAGATCGTAATTTTAATACATCTTTTTTTGATCCTGCTGGAGGAGGGGATCCTGTTCTGTTTCAG CATTTATTT >AEC60810/1-657 AEC60810 ACTTTGTATTTATTGTTTGGTATTTGATCTGCTATAATGGGAACGGCAATAAGAGTGATTATTCGAATTGAA TTAGGTCAAGTTGGAAGATTGTTGGGTGATGATCATTTATATAATGTAATTGTAACAGCACATGCTTTGGTT ATGATTTTTTTTATAGTTATACCGATTTTGATTGGTGGATTTGGAAATTGAATAGTTCCTTTGATGTTAGGT GCTCCAGATATAGCATTCCCACGTATAAATAATTTGAGATTTTGATTGCTTCCTCCATCATTATTTTTGTTA TTATTATCTTCTTTAACAGATGTAGGGGTTGGAGCCGGGTGAACTATTTATCCTCCTTTATCCTCTGGGGTT GGACATAGAGGGGGGGGGATGGATTTTGCTATTTTTTCTTTACATTTAGCAGGAGCTTCATCTATTATAGGG GCGATTAATTTTATTACAACAATTATTAATATGCGAAGATTTGGAATAACAATAGAACGTGTACCTTTATTT GTGTGATCAGTTCTTATTACTACTATTTTATTATTGCTTTCTTTACCTGTATTGGCTGGTGCTATTACTATA TTGTTGACTGATCGAAATTTCAATACTTCTTTTTTTGATCCTGCTGGAGGTGGTGATCCTATTTTGTTTCAA CATTTATTT >AEE92861/1-633 AEE92861 ------------------------TGATCTGCTATGGTAGGTACCGGAATAAGAGTAATTATTCGGTCTGAG TTGGGGCAAGTGGGAATATTATTAGGTGATGATCATATATATAATGTTATGGTTACTGCTCATGCTTTAGTA ATGATTTTTTTTATGGTAATGCCAATCATGATTGGAGGTTTTGGTAATTGATTATTGCCTTTAATGGTAGGA GCTCCTGATATGGCTTTTCCTCGTATAAATAATTTGAGTTTTTGATTGCTTCCTCCTTCTTTATTTTTGTTG GTGTTGTCTTCTTTAACAGATGTTGGGGTAGGGGCTGGTTGAACTATTTATCCTCCTTTGTCTTCGGGAGTT GGGCATGGAGGTGGGGGTATGGATTTTGCTATTTTTTCTTTGCATTTAGCTGGGGCTTCTTCTATTATGGGG GCGATTAATTTTATTACTACTATTATTAATATGCGTACAAATGGTATGACTATGGAGCGTGTGCCGTTGTTT GTGTGATCAGTATTAGTGACTGCTATTTTGTTATTGTTGTCTTTGCCAGTATTGGCGGGGGCTATTACAATA TTATTGACAGATCGTAATTTTAATACATCTTTTTTTGATCCTGCTGGAGGAGGGGATCCTGTTCTGTTTCAA CATTTATTT >AEE92860/1-648 AEE92860 ---------TTTGTTTTTGGAGCTTGATCTGCTATGGTAGGTACCGGAATAAGAGTAATTATTCGGTCTGAG TTGGGGCAAGTGGGAAGATTATTAGGTGATGATCATATATATAATGTTATGGTTACTGCTCATGCTTTAGTA ATGATTTTTTTTATGGTAATGCCAATCATGATTGGAGGTTTTGGTAATTGATTATTGCCTTTAATGGTAGGA GCTCCTGATATGGCTTTTCCTCGTATAAATAATTTGAGTTTTTGATTGCTTCCTCCTTCTTTATTTTTGTTG GTGTTGTCTTCTTTAACAGATGTTGGGGTAGGGGCTGGTTGAACTATTTATCCTCCTTTGTCTTCGGGAGTT GGGCATGGAGGTGGGGGTATGGATTTTGCTATTTTTTCTTTGCATTTAGCTGGGGCTTCTTCTATTATGGGG GCGATTAATTTTATTACTACTATTATTAATATGCGTACAAATGGTATGACTATGGAGCGTGTGCCGTTGTTT GTGTGATCAGTATTAGTGACTGCTATTTTGTTATTGTTGTCTTTGCCAGTATTGGCGGGGGCTATTACAATA TTATTGACAGATCGTAATTTTAATACATCTTTTTTTGATCCTGCTGGAGGAGGGGATCCTGTTCTGTTTCAA CATTTATTT >ADD09384/1-555 ADD09384 ------------------------------------------------------------------------ ------------------------------TATCAGCTATACAATGTATTAATTACCGCTCATGCTATAATT ATGGTATTTTTCATGATTATGCCAGCTTTATTTGGTGGATTTGGTAATTACTTTGTACCAATTTTAATAGGT GCCCCGGATATGGCTTTTCCTAGGCTAAATAATATAAGTTTTTGGCTACTTGTCCCTGCTTTTATATTATTA ATGCTGTCAGGTTTGGTTGATGGAGGAGCTGGTACTGGCTGGACACTGTATCCTCCTCTAAGTAGTATAGTA GGGCATCCTGGCGCTGCTGTCGATATGGCTATTTTAAGCTTACATCTTACAGGGCTTTCCTCCATTCTTGGT TCAATTAATATGATTGTCACTATCTTTAATATGAGAACTGATGGTATGGGGTTATTTGAAATGCCCTTATTT GTTTGGTCAATTTTGGTTACTGCCTTCTTGCTGATACTAGCAATTCCTGTGTTAGGGGGTGCAATAACCATG TTACTGACTGATCGAAATTTTGGTACTACTTTTTTCAAGCCTGATGGTGGCGGAGATCCAGTGTTATTTCAG CATTTATTT >ADJ82639/1-645 ADJ82639 ACTTTATATTTAATGTTTGGGGTTTGGTCAGCTATAATAGGAACTGCTATAAGAGTATTAATTCGAATGGAA TTAGGGAATCCTGGTAGATTGTTAGGTGATGATCATTTGTATAATGTTATAGTTACTGCTCATGCTTTTGTA ATAATTTTTTTTATAGTAATGCCTATTCTTATTGGAGGTTTTGGAAATTGATTAGTTCCTTTAATATTAGGA GCTCCAGATATATCATTTCCTCGAATAAATAATCTTTCTTTTTGATTATTACCTCCTTCTTTATTTTTGTTA TCTATATCTTCTATAGTAGAAATAGGAGTTGGGGCTGGGTGAACTGTTTATCCTCCTTTAGCGTCTACAGTT GGGCACATAGGAAATTCAATAGATTTTGCTATTTTTTCTCTTCATTTAGCTGGAGCTTCTTCTATTATAGGA GCTGTAAATTTTATTTCTACCATTATTAATATACGAATATTAGGAATATCTATAGAGAAGGTTCCTCTTTTT GTTTGATCAGTTTTAATTACAGCAGTATTATTATTACTTTCTTTACCTGTTTTAGCAGGTGCTATTACTATA TTATTAACAGATCGAAATTTTAATACTTCTTTTTTTGATCCTGCTGGGGGAGGAGATCCTAATTTATTT--- --------- >ADQ21240/1-648 ADQ21240 AGATTATATTTTGTTTTTGGGGCTTGAGCTGCTATAGTAGGAACAGCAATAAGAGTATTAATTCGTGTTGAG TTGGGACAAACTGGTAGTTTGTTAGGGGATGATCAGTTGTATAATGTTATTGTTACGGCTCATGCTTTTGTA ATAATTTTTTTTATAGTTATGCCTATTTTAATTGGGGGTTTTGGAAATTGGCTGATTCCACTAATACTAGGA GCTCCGGATATAGCTTTCCCTCGTATAAATAATTTGAGATTTTGGCTTTTACCCCCTTCTTTATTATTACTG TTTATTTCAAGCATAGATGAGATAGGAGTGGGGGCGGGATGAACGGTTTACCCCCCTCTTGCCTCTTTAGAG GGACATTCTGGTAGTTCAGTAGATTTTGCTATTTTTTCTTTACACTTAGCTGGAGCGTCTTCTATTATAGGG GCTATTAATTTTATTTCCACAATTTTGAATATACGGGGTTATGGAATATCTATAGAAAAAGTACCTTTATTT GTTTGGTCCGTGTTAATTACAGCTGTATTATTATTGTTATCTCTTCCTGTGTTAGCTGGGGCTATCACAATA TTACTGACGGATCGTAATTTTAATACTTCATTTTTTGATCCTTGTGGGGGGGGGGATCCTGTTTTGTTTCAA --------- >AEE92882/1-657 AEE92882 ACGTTATATTTTGTTTTTGGAGCTTGATCTGCTATGGTAGGGACCGGAATAAGAGTAATTATTCGGTCTGAG TTGGGGCAAGTGGGGAGATTGTTGGGTGATGATCATATATATAATGTTATTGTAACTGCTCATGCTTTAGTA ATGATTTTTTTTATGGTAATGCCAATCATGATTGGAGGTTTTGGTAATTGATTACTGCCTTTAATAGTAGGA GCTCCTGATATGGCTTTTCCTCGTATAAATAATTTGAGTTTTTGATTGCTTCCACCTTCTTTATTTTTGTTG GTGTTGTCTTCTTTAACAGATGTTGGGGTAGGGGCTGGTTGAACTATTTATCCTCCTTTGTCTTCGGGAGTT GGGCATGGAGGTGGGGGTATGGATTTTGCTATTTTTTCTTTGCATTTAGCTGGGGCTTCTTCTATTATGGGG GCGATTAATTTTATTACCACTATTATTAATATGCGTACAAATGGTATAACTATGGAGCGTGTGCCGTTGTTT GTGTGATCAGTATTAGTGACTGCTATTTTGTTATTATTGTCTTTACCAGTATTGGCGGGGGCTATTACGATA TTACTAACAGATCGTAATTTTAATACATCTTTTTTTGATCCTGCTGGAGGAGGGGATCCTGTTCTGTTTCAG CATTTATTT >ADW58691/1-657 ADW58691 ACTTTATATTTAATATTTGGAGCTTGATCTGCTATAGTAGGGACTGCTATAAGAGTGTTAATTCGAATAGAA TTAGGTCAATCTGGAAGACTTTTAGGTGATGATCATTTATATAATGTTGTAGTTACTGCACATGCTTTTGTT ATAATTTTTTTTATAGTTATACCTATTTTGATTGGTGGTTTTGGAAATTGGTTAGTTCCTTTAATATTAGGT GCTCCTGATATAGCTTTTCCTCGAATAAATAATTTAAGTTTTTGATTATTACCTCCTTCTTTATTTTTATTA TTTATTTCTTCTATAGTTGAAATAGGAGTTGGAGCAGGATGAACAGTTTATCCTCCATTGGCATCTAGTGTA GGTCATATGGGAAGTGCAATAGATTTTGCTATTTTTTCATTACATTTGGCTGGTGCTTCTTCTATTATAGGA GCAGTAAATTTTATTACTACTATTATTAATATACGTTCTCATGGAATAAGAATAGAAAAAGTTCCTTTATTT GTTTGATCAGTTTTAATTACAGCTATTTTGTTGTTATTATCTTTACCTGTTTTAGCAGGTGCTATTACTATA TTATTAACTGATCGTAATTTTAATACTTCTTTTTTTGATCCTGCTGGAGGAGGAGATCCTATTTTATTTCAA CATTTATTT >ADW58631/1-657 ADW58631 ACTTTATATTTAATATTTGGAGCTTGATCTGCTATAGTAGGGACTGCTATAAGAGTGTTAATTCGAATAGAA TTAGGTCAATCTGGAAGACTTTTAGGTGATGATCATTTATATAATGTTGTAGTTACTGCACATGCTTTTGTT ATAATTTTTTTTATAGTTATACCTATTTTGATTGGTGGTTTTGGAAATTGGTTAGTTCCTTTAATATTAGGT GCTCCTGATATAGCTTTTCCTCGAATAAATAATTTAAGTTTTTGATTACTACCTCCTTCTTTATTTTTATTA TTTATTTCTTCTATAGCTGAAATAGGAGTTGGAGCAGGATGAACAGTTTATCCTCCATTGGCATCTAGTGTA GGTCATATAGGAAGTGCAATAGATTTTGCTATTTTTTCATTACATTTGGCTGGTGCTTCTTCTATTATAGGA GCAGTAAATTTTATTACTACTATTATTAATATACGTTCTCATGGAATAAGAATAGAAAAAGTTCCTTTATTT GTTTGATCAGTTTTAATTACAGCTATTTTGTTGTTATTATCTTTACCTGTTTTAGCAGGTGCTATTACTATA TTATTAACTGATCGTAATTTTAATACTTCTTTTTTTGATCCTGCTGGAGGAGGAGATCCTATTTTATTTCAA CATTTATTT >ACM89220/1-657 ACM89220 ACTTTATATTTTTTATTTGGTACTTGATCAGCAATAATTGGTACAGCAATAAGTGTTTTAATTCGTGTTGAA CTAGGATTTTCTGGAAGATTTTTAGGTGATGATCATTTATATAATGTAATTGTTACTGCTCATGCTTTTATT ATAATTTTTTTTATAGTTATACCTATTTTAATTGGTGGTTTTGGAAATTGGTTAGTTCCTTTAATATTAAGA GCTCCAGATATAGCTTTTCCTCGTATAAATAATTTAAGATTTTGGTTACTACCTCCTTCGTTATTATTGTTA TTTATTTCTTCTATGGTTGAAATCGGAGTTGGAGCAGGGTGGACTATTTATCCTCCTTTATCTTCTTCTGTG GGTCATTCTGGTGCATCTATGGATTTTGCAATTTTTTCTCTTCATTTAGCTGGTGCTTCTTCTATTATAGGT GCTATTAATTTTATTTCAACAATTATTAATATACGACCTTATGGTATAAGAATAGAAAAGATTCCTTTATTT GTATGATCTGTATTAATTACAGCTGTCTTATTATTATTATCATTACCAGTATTAGCTGGGGCTATTACTATA CTTTTAACTGATCGTAATTTTAATACTTCTTTTTTTGATCCAGCTGGGGGTGGGGATCCAATTTTATTTCAG CATTTATTT >AEE92867/1-642 AEE92867 ---------------TTTGGGGCTTGATCTGCTATGGTAGGTACCGGAATAAGAGTAATTATTCGGTCTGAG TTGGGGCAAGTGGGAAGATTATTAGGTGATGATCATATATATAATGTTATGGTTACTGCTCATGCTTTAGTA ATGATTTTTTTTATGGTAATGCCAATCATGATTGGAGGTTTTGGTAATTGATTATTGCCTTTAATGGTAGGA GCTCCTGATATGGCTTTTCCTCGTATAAATAATTTGAGTTTTTGATTGCTTCCTCCTTCTTTATTTTTGTTG GTGTTGTCTTCTTTAACAGATGTTGGGGTAGGGGCTGGTTGAACTATTTATCCTCCTTTGTCTTCGGGAGTT GGGCATGGAGGTGGGGGTATGGATTTTGCTATTTTTTCTTTGCATTTAGCTGGGGCTTCTTCTATTATGGGG GCGATTAATTTTATTACTACTATTATTAATATGCGTACAAATGGTATGACTATGGAGCGTGTGCCGTTGTTT GTGTGATCAGTATTAGTGACTGCTATTTTGTTATTGTTGTCTTTGCCAGTATTGGCGGGGGCTATTACAATA TTATTGACAGATCGTAATTTTAATACATCTTTTTTTGATCCTGCTGGAGGAGGGGATCCTGTTCTGTTTCAA CATTTATTT >ADH12119/1-645 ADH12119 ACTTTATACTTGGTTTTTGGTGCTTGAGCGGCTATGGTTGGAACTGCAATAAGTGTTTTAATTCGAATTGAG TTGGGGCAATCTGGTAGATTTATGGGAGATGATCAGTTGTATAATGTTATTGTAACTGCTCATGCTTTTGTT ATAATTTTTTTTATGGTTATGCCTATTTTGATTGGGGGCTTTGGTAATTGACTGGTTCCTTTGATGTTGGGG GCTCCTGATATGGCTTTTCCTCGCATGAATAATTTAAGGTTTTGATTATTGCCTCCTTCTTTATTTTTATTA TTTATTTCTTCTATGGTGGAAATAGGGGTTGGGGCTGGTTGAACGATCTACCCTCCTTTAGCGTCTCTAGAA GGACATTCAGGAAGTTCGGTTGATTTTGCCATTTTTTCTTTGCATTTGGCTGGGGCCTCTTCTATTATAGGG GCTATTAATTTTATTTCTACAATTTTGAATATACGGTCTTATGGGATGTCTATGGAAAAAGTTCCTTTGTTT GTTTGGTCGGTTTTAATTACTGCTGTTTTGCTCCTATTATCACTTCCGGTTTTAGCTGGGGCTATCACTATG TTATTAACTGATCGAAATTTTAATACATCGTTTTTTGATCCTTCGGGGGGAGGGGATCCTATTTTTTTT--- --------- 2013-02-19 10:49:56.589 UTC Multiple Sequence Alignment in Fasta format 2013-02-19 10:49:24.341 UTC Possible_Partition00 Partitioning of the MSA using nexus/raxml syntax. Define at least 2 partitions. Partition could define codon positions and/or gene boundaries and/or domains 2013-08-09 10:46:18.147 UTC Gene1_pos1 = 1-657\3; Gene1_pos2 = 2-657\3; Gene1_pos3 = 3-657\3; 2013-02-19 10:48:53.331 UTC Statistical_Criterium00 AIC 2013-05-16 14:39:40.352 UTC What statistical criterium should be used to compare different models? AIC = Aikake information Criterium AICc =Aikake information Criterium correct per sample size BIC = Bayesian Information Criterium 3 possible values: AIC, AICc, or BIC 2013-05-16 14:39:16.341 UTC Number_of_runs00 2 2013-05-16 14:41:18.758 UTC Number of independent runs to check convergence of the markovian integration necessary to perform bayesian phylogenetic inference. Minimum value 2. Always an integer 2013-08-09 10:47:12.935 UTC Number_of_MCMCMC_generations00 Number of Generation for each run of the markovian integration necessary to the phylogenetic inference. The convergence test (GeoKS) will tell post hoc if the number was sufficient. If is not the case try with a larger number following the educated guess of GeoKS 2013-08-09 10:48:48.14 UTC 100000 2013-05-16 14:42:40.370 UTC File_name00 Filename for nexus input file 2013-08-09 10:49:26.885 UTC pippo 2013-05-16 14:43:50.324 UTC Linking_branches00 Should models assume that branches in the tree are linked or unlinked across alignment parts? Two possible strings: linked unlinked 2013-08-09 10:49:59.869 UTC linked 2013-05-16 14:37:51.905 UTC SampleSize00 Sample Size from the Posterior Distribution to test fit of model on Data. This integer should be smaller than number of generation divided by 100. 2013-05-17 12:50:34.889 UTC 100 2013-05-17 12:50:37.808 UTC Email00PartitionFinderOutput0 Main output of PartitionFinder, where the preffered partitioned model is described 2013-06-14 15:59:48.203 UTC PartitionFinderDetails0 Path were to retrieve all the detials of the partitionfinder software 2013-06-14 15:59:15.966 UTC Log1NameFile0SessionID0JobID0 Number to be used to retrive the phylogenetic inference . 2014-07-04 08:51:45.414 UTC SelectingEvolutionaryModelWithPartFinderStatCriterium0PossiblePartition0MSA_fasta0NumberRuns0MCMCMCGenerationNumber0LinkingBranches0Token0Log00Path00MrBayesInput00PartitionFinderOuput00net.sf.taverna.t2.componentcomponent-activity1.5net.sf.taverna.t2.component.ComponentActivity http://www.myexperiment.org BayesianPhylogeneticInference SelectingEvolutionaryModelWithPartFinder 15 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeJSTWebDav3InputInputBody0Token0File_name0REST_Service_redirection00net.sf.taverna.t2.componentcomponent-activity1.5net.sf.taverna.t2.component.ComponentActivity http://www.myexperiment.org JSTInteraction JSTWebDav3Input 3 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeRandGenout00net.sf.taverna.t2.activitieslocalworker-activity1.5net.sf.taverna.t2.activities.localworker.LocalworkerActivity out 0 0 workflow org.embl.ebi.escience.scuflworkers.java.TestSometimesFails UserNameHere 2013-05-27 13:52:26.399 UTC net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeNoSpacestring0out100net.sf.taverna.t2.activitiesbeanshell-activity1.5net.sf.taverna.t2.activities.beanshell.BeanshellActivity string 0 text/plain java.lang.String true out1 0 0 workflow net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeTargetOnlystring0out100net.sf.taverna.t2.activitiesbeanshell-activity1.5net.sf.taverna.t2.activities.beanshell.BeanshellActivity string 0 text/plain java.lang.String true out1 0 0 workflow net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeText_constantvalue00net.sf.taverna.t2.activitiesstringconstant-activity1.5net.sf.taverna.t2.activities.stringconstant.StringConstantActivity MrBayes_16CPUs net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeREST_Servicename0mail0arguments0responseBody00net.sf.taverna.t2.activitiesrest-activity1.5net.sf.taverna.t2.activities.rest.RESTActivity GET http://alicegrid17.ba.infn.it:8080/INFN.Grid.RestFrontEnd/services/QueryJob/InsertJobs?NAME={name}&arguments={arguments}&mail={mail} application/xml application/xml String false false false false true mail java.lang.String arguments java.lang.String name java.lang.String net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeXPath_Servicexml_text0firstNode00net.sf.taverna.t2.activitiesxpath-activity1.5net.sf.taverna.t2.activities.xpath.XPathActivity <?xml version="1.0" encoding="UTF-8"?> <Job><Name>blast</Name><Flag>7772590c-d7ab-4b76-98b9-aa293c6c34fe</Flag><JobsID><JobId>454118</JobId></JobsID></Job> /Job/JobsID/JobId net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize 1 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry 1.0 1000 5000 0 net.sf.taverna.t2.coreworkflowmodel-impl1.5net.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeSelectingEvolutionaryModelWithPartFinderStatCriteriumStatistical_CriteriumSelectingEvolutionaryModelWithPartFinderPossiblePartitionPossible_PartitionSelectingEvolutionaryModelWithPartFinderMSA_fastaMSA_fastaSelectingEvolutionaryModelWithPartFinderNumberRunsNumber_of_runsSelectingEvolutionaryModelWithPartFinderMCMCMCGenerationNumberNumber_of_MCMCMC_generationsSelectingEvolutionaryModelWithPartFinderLinkingBranchesLinking_branchesSelectingEvolutionaryModelWithPartFinderTokenRandGenoutJSTWebDav3InputInputBodySelectingEvolutionaryModelWithPartFinderMrBayesInputJSTWebDav3InputTokenRandGenoutJSTWebDav3InputFile_nameNoSpaceout1NoSpacestringFile_nameTargetOnlystringJSTWebDav3InputREST_Service_redirectionREST_ServicenameText_constantvalueREST_ServicemailEmailREST_ServiceargumentsJSTWebDav3InputREST_Service_redirectionXPath_Servicexml_textREST_ServiceresponseBodyLogSelectingEvolutionaryModelWithPartFinderLogPartitionFinderOutputSelectingEvolutionaryModelWithPartFinderPartitionFinderOuputPartitionFinderDetailsSelectingEvolutionaryModelWithPartFinderPathNameFileTargetOnlyout1SessionIDRandGenoutJobIDXPath_ServicefirstNode 5e1346e0-74f7-4d4b-8b71-e1ebbae58d54 2013-05-16 14:44:06.35 UTC ec97812d-762d-49bd-9044-63be0669e046 2013-06-06 14:28:24.400 UTC ca0f1d3c-efbd-488d-8abd-93fc869c9727 2013-12-12 13:56:29.479 UTC f0ff22ab-ea1d-4b66-a2a1-1585e921bfb0 2014-03-19 13:33:54.871 UTC f2dc5113-49a1-48b9-a380-89e41fb0b75f 2013-12-12 15:30:11.454 UTC 83c71b7c-d10e-4508-a70b-aef98c7621de 2014-03-19 09:38:14.166 UTC 81f78894-7bd6-4ff5-8eb8-dcda2f0f12bf 2013-06-13 09:17:43.404 UTC 0df96ea8-813d-432c-b643-b9e88dc392e2 2013-06-14 15:53:14.431 UTC 99b41795-d4e8-401a-a78a-1045de516057 2013-12-12 13:49:51.929 UTC b65fb5fb-4c3b-40ed-a1e5-d2885cb2a39b 2013-02-20 12:18:35.247 UTC 79cef4c8-aa90-42eb-bbbc-547d0c65cdf6 2013-06-13 09:52:48.451 UTC 3c0f7bc7-b951-4288-98b6-55cae1470d64 2013-03-28 11:13:40.711 UTC 1ac652de-6758-4e37-af2e-1afeb6b4901e 2013-05-17 13:47:57.443 UTC fe7143ba-65fc-4e2b-bff7-86c634452bc7 2013-12-17 15:05:53.332 UTC 28272e3a-e84b-43b1-86d1-719387da9aa6 2013-02-20 09:36:45.90 UTC fdebe370-df01-45ee-b953-d307ea7f7611 2013-02-20 12:57:15.288 UTC 2250be3a-4d4e-4514-aafa-aad35e4446c6 2013-12-04 14:56:15.61 UTC 89bccc8c-5469-44f8-9dae-145a71ec5eea 2013-12-11 14:31:01.7 UTC c588ab33-7f5a-459a-8fad-f9d4bac96b63 2013-02-20 11:58:19.43 UTC 5eccdbe8-ccfc-41d0-8148-4a61ff13a73a 2014-04-09 14:36:31.297 UTC 17dddb23-51c4-40ae-b2cc-3df209d2c890 2013-06-06 13:15:51.55 UTC f1b5bc6c-97b0-4d1b-b4d8-75d4c0c6ccff 2013-05-17 13:43:00.599 UTC dbd742de-f68a-4032-b7ff-7cd4d9ebc48c 2013-12-12 15:43:48.738 UTC BioVeL – Biodiversity Virtual e-Laboratory Workflow Documentation Name:Perform Short Bayesian Phylogenetic Inference Capacities Programme of Framework 7: EC e-Infrastructure Programme – e-Science Environments - INFRA-2011-1.2.1 Grant Agreement No: 283359 Project Co-ordinator: Mr Alex Hardisty Project Homepage: [http://www.biovel.eu][1] [1]: http://www.biovel.eu ## 1 Description The Pack contain 3 workflows that perform and validate bayesian phylogenetic inference that differ from the kind of input. The pack is called short because the worlflow require that the user need to keep taverna engine always on for the the time of the analysis. This could be quite problematic for large analysis. In this case search help in the "Perform Long Bayesian Phylogenetic Inference" pack In this pack there are 3 workflows: 1) User locally formatted input file (for details in nexus format for mrbayes [http://mrbayes.sourceforge.net/wiki/index.php/Manual_3.2][2]) 2) User is helped by a GUI (graphical user interface) to define an partitioned evolutionary model on user defined MSA (multiple sequence alignment) 3) PartitionFinder define best candidate partitioned evolutionary model based on proposed maximum set of possible partition Note: a partitioned model is a model that allow different groups of sites (i.e. columns of the MSA) to follow the rule or parameters set of different evolutionary models. MrBayes allows that some of the parameters to be shared across partitions while other being different. The submit workflow 2 based on the GUI allow to fully take advantage of this features while the submit workflow 3 based on PartitionFinder allow to share across partition optionally branch length and always the topology All 3 workflows perform 2 validations on the inference, one on the numerical integration (GeoKS) and one on the fit of the model (Posterior Predictive Test) [2]: http://mrbayes.sourceforge.net/wiki/index.php/Manual_3.2 ## 2 General **2.1 Name of the workflow and myExperiment +BiodiversityCatalogue identifiers** Name: Perform Short Bayesian Phylogenetic Inference Download info: [http://www.myexperiment.org/packs/371.html][3] BiodiversityCatalogue entry: **2.2 Date, version and licensing** Last [updated:21/02/13][4] @ 09:08:18 Version: 2 Licensing: Creative Commons Attribution ShareAlike CC-BY- SA **2.3 How to cite this workflow** These results come from the processing of data (personal source or others--cite which one, i.e. ENA) through BioVeL's services ([www.biovel.eu][5]). BioVeL is funded by the EU’s Seventh Framework Program, grant no. 283359. Use the article [http://journal.embnet.org/index.php/embnetjournal/article/view/557][6] [3]: http://www.myexperiment.org/packs/371.html [4]: http://updated:21/02/13 [5]: http://www.biovel.eu [6]: http://journal.embnet.org/index.php/embnetjournal/article/view/557 ## 3. Scientific Specifications **3.1. Keywords:** Phylogenetic inference, Bayesian, MrBayes, Posterior Predictive test, Convergence test **3.2. Scientific workflow description:** The different step for a complete phylogenetic inference are in this pack divided as following: 1. Define model framework 2. Estimate parameters of the model framework with a Markovian Integration within a Bayesian framework 3. Validate the convergence of the Markovian Integration with a test on the overlap of the tree posterior distribution of two or more independent runs (GeoKS) 4. Test the adequacy or goodness of fit of the model with a posterior predictive test **3.2.1 Define model framework:** MrBayes allows to define partitioned model of evolution of the character of the MSA, to perform a given phylogenetic inference. A Partitioned model is a model that allow different groups of sites (i.e. columns of the MSA) to follow the rule or parameters set of different evolutionary models. Within MrBayes is possible to define 5 group of parameters that can be shared or not across user defined group of sites 1. Substitution Matrix 2. State frequencies 3. Site Specific rates 4. Branch lengths 5. Topology Workflow 1 "All is ready to run". leave the user the duty to define and format a model using the criteria and tool preferred. Workflow 2 "Select Model" based on a GUI help the user to define a model that share or not across user defined partition independently all 5 groups of parameters, taking care of the formatting. Workflow 3 "Select Model for Me" based on PartitionFinder ([http://www.robertlanfear.com/partitionfinder/][7]) allows to define the best partitioning of the sites based on a starting maximal partitioning proposed by the user, but decision of the sharing or not across partition is done together for groups 1, 2, and 3 while branch lengths could be shared across all partition or none (no sharing across some partitions) and topology need to be shared across all sites. [7]: http://www.robertlanfear.com/partitionfinder/ ![][8] Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > PhyloInfWFColorAll-renzo.png" data-location="BioVeL User Documentation > Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > PhyloInfWFColorAll-renzo.png"> **3.2.2 Estimate parameters of the model framework with a Markovian Integration within a Bayesian framework:** All 3 submit workflows send the input defined and formatted differently to the same service that start a MrBayes run. (ref 1,2,3) **3.2.3 Validate the convergence of the Markovian Integration with a test on the overlap of the tree posterior distribution of two or more independent runs (GeoKS):** The result of the MrBayes service are loaded by the retrieval workflow that perform a test of convergence based on the on the overlap of the tree posterior distribution of two or more independent runs. Details on this link **3.2.4 Test the adequacy or goodness of fit of the model with a posterior predictive test**: The service written in python read each estimation of set of parameters from a sub-sample of the overall posterior distribution and simulated (using evolver utility from PAML 1.4 package) new MSA. The simulated distribution is compared to the original MSA based on the sum of the sites entropy as proposed by Bollback (2002)[ref 4] An Histogram is draw for the distribution of the complexities (log of sum of sites entropy or maximal possible loglikelihood score) of the simulated data using the posterior distribution parameters compared with observed data complexity. The 1-alpha high posterior density of the distribution show the region where simulate data complexity match the observed one. Larger observed complexity indicates model too simplistic, while the contrary indicates overparametrization of the model. [8]: /download/attachments/8619115/PhyloInfWFColorAll-renzo.png?version=1&modificationDate=1393242192541&api=v2 (BioVeL User Documentation > Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > PhyloInfWFColorAll-renzo.png) **3.2.5 Visualization of the consensus inference** The newick representation of the consensus of the inference is sent to the ITOL web service ([see details at http://itol.embl.de/][9]). The service allows to visualize an interactive graphical representation of the tree. After manipulation and editing the tree can be exported in several graphical format or downloaded as newick or phyloxml format. Relaoding the tree with this format togheter with user defined annotation table allows very powerfull graphical representation of the tree (see details on [http://itol.embl.de/help/help.shtml][10]) [9]: http://itol.embl.de/ [10]: http://itol.embl.de/help/help.shtml ## 4. Technical Specifications **4.1. Execution environment and installation requirements** The 3 workflows are all tested on taverna workbench. They should be able to be loaded on Taverna Lite **4.2. Taverna installation, including updates and plug-ins** [Taverna workbench installation][11] [Interaction plug-in][12] **4.2.1 Taverna Dependencies** The all 3 workflow require a local R serve to allow to draw the graph output of the Posterior Predictive Test. The Workflow 3 based on Partition Finder, requires a python interpret installed on the path and accessible to Taverna engine. No python module is required by the script and although tested only with python 2.7 should work also with older python. [11]: https://wiki.biovel.eu/display/doc/Taverna+Workbench [12]: https://wiki.biovel.eu/display/doc/Customising+for+BioVeL#CustomisingforBioVeL-InstallingtheInteractionplug-in ## 5. Tutorial - how to do it **5.1. Introduction** The user depending of the 3 different scenarios presented in 3.2.1 will choose one of the 3 submit workflows. **5.2. Input data** **5.2.1. Data preparation/format** Workflow 1 the format for the input (called"NexusFile") is nexus with data block and mrbayes block. Within the data block the MSA is specified together with the type of possible states, while in the mrbayes block the user need to define the evolutionary model and the parameters for the markovian integration ( number of generation, temperature, number of chain for the metropolis coupled part of the algorithm, and number of replicates runs to control convergence). See details in [http://mrbayes.sourceforge.net/wiki/index.php/Manual_3.2][13] Workflow 2 and 3 require a MSA in aligned multifasta format (see [http://en.wikipedia.org/wiki/FASTA_format][14]). Recognized gap character is "-" Workflow 3 require also a text in which user define maximum set of parts fo the alignment, meaning the maximal subdivision in group that sites could have. Mind the Partitionfinder try all combinatorial change possible and is not adivsed to propose more than 14 parts. [13]: http://mrbayes.sourceforge.net/wiki/index.php/Manual_3.2 [14]: http://en.wikipedia.org/wiki/FASTA_format Syntax to define partition is the following: Each part is defined by a alpha numeric string with no space (the name) connected by an equal sign to the list of sites to be included. Description end with the semicolon sign. A range of sites are described as start and ending sites divided by minus sign (i.e. gene1= 10-30;) with both start and end included Discontinue sections are divided by a space (i.e. gene1= 10-30 34 40;) Range with a step (i.e.“every third base”) are expressed with a slash (i.e. gene1= 10-30\3;) So a complex but realistic example could be: utr5= 1-30; cds_pos1 = 30-200/3 400-500/3; cds_pos2 = 31-200/3 399-500/3; cds_pos3 = 32-200/3 398-500/3; intron= 200-397; utr3= 501-600; **5.2.2. Other input ** file name: name for the nexus file produced on the basis of partitionFinder results number of MCMCMC generations: integer indicating number of generation to be used in the markovian integration number of runs: integer indicating how many indipendent runs of mrbayes need to be performed ( the more the better convergence is detected branch length are linked or unlinked across partition: see 3.2.1 for details what criterium to be used by PartitionFinder: the criteria a AIC, AICc and BIC. All of them are information criteria. In general statistical framework AIC should be always prefferrd to AIC but in phylogenetics there are dispute on how to count constant sites. If your MSA have very few constant sites or you selected your locus randomly use AICc without doubt. For large MSA AIC and AICc give similar results. **5.3. Select Dialogue boxes** For each web services called a message tell the user the name and the number of the job id to the user. The message disappear after the user would push any of the buttons or if another web services is called before any action is taken. The message allows the user to know at what point of the workflow is and gives the job id number that would allow the service centre to identify the job, in case of failure. ![][15] Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > Schermata 2013-08-09 alle 15.53.43.png" data-location="BioVeL User Documentation > Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > Schermata 2013-08-09 alle 15.53.43.png"> Workflow 1 does not have specific dialog box Worklfow 2 have a large and complex self explanatory web page. To start to use paste a aligned multifasta file in the only visible text window and click confirm. Following choice are explained by yellow bottom on the side of each question or pull down menu Workflow 3 have following dialog box: [15]: /download/attachments/8619115/Schermata%202013-08-09%20alle%2015.53.43.png?version=1&modificationDate=1376213644377&api=v2 (BioVeL User Documentation > Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > Schermata 2013-08-09 alle 15.53.43.png) partition to be selected: this windows allows to choose a subset of partition to be used. At the moment is not relevant but coupling this workflow with alignment this windows could be not redundant ![][16] Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > Schermata 2013-08-09 alle 15.39.49.png" data-location="BioVeL User Documentation > Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > Schermata 2013-08-09 alle 15.39.49.png"> **5.4. Save data/results** The 3 workflows have the following outputs: [16]: /download/attachments/8619115/Schermata%202013-08-09%20alle%2015.39.49.png?version=1&modificationDate=1376213738892&api=v2 (BioVeL User Documentation > Define, perform and validate a Bayesian Phylogenetic Inference - Taverna engine always on or from BioVeL Portal > Schermata 2013-08-09 alle 15.39.49.png) **Plot** Description: Result of the Posterior Predictive test. Histogram of the distribution of the complexities (log of sum of sites entropy or maximal possible loglikelihood score) of the simulated data using the posterior distribution parameters compared with observed data complexity. The 1-alpha high posterior density of the distribution show the region where simulate data complexity match the observed one. Larger observed complexity indicates model too simplistic, while the contrary indicates overparametrization of the model **Newicktree** Description: small xml with tag res with one or more tag tree each one with a body that contain a tree in netwick format. each tree represent the consensus for a given partition of group of partition in the same order that are cited in the nexus input file of mrbayes **Geoks** Description: Result of the GeoKS test of convergence. XML format **Phyloinferenceoutput** * Description: The output of the consensus service is a path were to obtain a zipped folder that includes all output from phylogenetic inference and the one of the consensus **Viewtree*** Description: Link to visualize consensus Tree of phylogenetic inference. It could be more than one link if the model assume more than one tree (combination topology + branch length set). Use of the figure in the link below should be always accompagned by appropriate citation: Letunic I and Bork P (2011) Nucleic Acids Res doi: 10.1093/nar/gkr201 Interactive Tree Of Life v2: online annotation and display of phylogenetic trees made eas **Mrbayesoutput*** Description: original output of mrbayes **Detailspptest** Description: Numeric Result of the Posterior Predictive test. **Partitionfinderoutput** Description: Main output of PartitionFinder, where the preffered partitioned model is described **Log** Description: Log file of all application used in the workflow. For each external website is reported the name of the application , the jobid required to track error on the service provvider and the last 200line of the standardouput+standardError of the application as view by the local system where the job was run. **Partitionfinderdetails*** Description: Path were to retrieve all the detials of the partitionfinder software **Geoksdetails*** Description: Path were to get all details of convergence test calculation. Ouput with * are also exposed on a downloadable link in the web browser as soon as they are produced **5.5. Results analysis** If the GeoKS test fail, the p-value is lower of the risk accepted by the user, the workflow stop and do not perform the posterior predictive test and the tree consensus calculation. User is invited to look at GeoKS result and increase the generation number of at least 1.5 times. If the GeoKS test do not fail, the p-value is higher of the risk accepted by the user, the user is invited to check that no more generation are advised by GeoKS. In fact the program advise the user for more generation if less that 300 Effective Sample Size (ESS) Tree are present in the posterior distribution. With less than 300 ESS trees the test do not guarantee to have sufficient power to detect correctly convergence. Then the user should look at the plot output and check if the red line (observed MSA complexity) is within the HSD of the distribution. If the red line is on the right of the distribution a more complex model need to be taken in consideration. if the red line is on the left of the distribution it could be than a more simple model could be entertained, and branch support are excessively conservative. Once the two tests are positive the user could inspect the consensus tree on ITOL, decorate at will and print on file the tree for a publication. The naked netwick tree could be also extracted using the option save tree from ITOL or directly from the output port newick ## 6. Support For questions with using the workflow, please write [support@biovel.eu][17]. For definitions of technical and biological terms, please visit the BioVeL glossary page: [https://wiki.biovel.eu/display/BioVeL/Glossary][18] [17]: mailto:support@biovel.eu [18]: https://wiki.biovel.eu/display/BioVeL/Glossary ## 7. Bibliography 1. Huelsenbeck JP, Larget B, Miller RE, Ronquist F. Potential applications and pitfalls of Bayesian inference of phylogeny. Systematic biology. 2002;51(5):673–88. Available at: [http://sysbio.oxfordjournals.org/content/51/5/673.abstract][19] [Accessed January 29, 2013]. 2. Huelsenbeck JP, Ronquist F. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics (Oxford, England). 2001;17(8):754–5. Available at: [http://www.ncbi.nlm.nih.gov/pubmed/11524383][20] [Accessed January 29, 2013]. 3. Altekar G, Dwarkadas S, Huelsenbeck JP, Ronquist F. Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference. Bioinformatics (Oxford, England). 2004;20(3):407–15. Available at: [http://www.ncbi.nlm.nih.gov/pubmed/14960467][21]. 4. Bollback JP. Bayesian Model Adequacy and Choice in Phylogenetics. Molecular biology and evolution. 2002;19(7):1171–1180. [19]: http://sysbio.oxfordjournals.org/content/51/5/673.abstract [20]: http://www.ncbi.nlm.nih.gov/pubmed/11524383 [21]: http://www.ncbi.nlm.nih.gov/pubmed/14960467 2014-07-04 09:12:08.646 UTC 4ddc4723-5f66-4039-9399-2dde19b4c44a 2013-06-13 09:48:49.211 UTC 51c43011-e9bc-4141-897c-901ae6a00b5a 2013-07-01 13:52:59.199 UTC 2a1433ad-3a0a-4fce-bc1b-1e1d203e2f4f 2013-05-17 14:01:00.177 UTC 2813a541-7010-4115-84db-39c44a20c425 2013-02-20 14:17:55.124 UTC 831b2dc7-d4c8-4eb9-8deb-9af26f4fee4a 2013-06-14 14:38:54.931 UTC a2b8e237-d257-4e69-8a6c-9f030c5e5c38 2013-12-11 21:46:06.359 UTC 3aad0169-4dfe-4ed9-8f5e-f3149e2843a0 2013-12-16 14:43:52.346 UTC be4aa380-72a5-46cf-9f80-6afe4881de5b 2013-07-02 13:29:06.880 UTC 2a270f77-438b-4cc0-aaa9-b301f65aed51 2014-07-04 09:16:11.834 UTC saverio vicario giacinto donvito bachir balech 2013-02-19 10:54:10.67 UTC b81cebf4-6434-4ac5-9504-1bb7950bc6cc 2014-07-04 08:52:57.802 UTC cd487d97-579b-41f4-8bc6-88371a1703df 2013-02-19 10:52:29.614 UTC d55a4a20-af19-4ee1-b99c-913455333ef1 2013-05-17 13:24:34.551 UTC b2b1fc13-6cfc-4307-b6b1-d1cfc3176850 2013-12-12 13:51:01.345 UTC 6d9b18d8-d7c4-4b82-b62d-99564eae080c 2013-06-20 15:46:33.623 UTC 7aadccb0-4a1b-4486-9b1d-9d39d871405f 2013-06-13 09:16:43.390 UTC e8c5e31c-7e92-44ec-bcda-6567fea6030b 2013-12-04 11:57:56.534 UTC 2dbbc8b7-8bb6-4174-995e-bb3e1097a784 2013-03-28 11:31:59.717 UTC 3d27e111-0ccf-491f-8619-a0d5c9c9b530 2013-12-12 15:41:59.623 UTC ac29b67c-ac1b-430a-afda-982bce0fc451 2013-02-20 14:14:06.10 UTC 46ead065-bb6f-41d4-af8c-bb7ccffc75e3 2013-02-19 10:50:28.376 UTC 5dc1fb99-d6dc-453e-a1b5-4cb0621ec44c 2013-06-14 15:09:52.865 UTC 495997c9-1ba0-4711-b6f8-548773933cd8 2013-03-28 09:14:07.619 UTC c7d70b9c-f3e6-4c25-b351-d638cc13fa1d 2013-12-11 16:13:58.995 UTC cf28931d-4d12-42f4-9e45-628d73a2fb78 2013-12-11 21:42:42.535 UTC 69b6d526-4e4d-4fae-bd87-751f43e25d88 2013-12-12 12:23:20.112 UTC 2e735a0a-988b-4bba-9e5d-f02944cd0d24 2013-02-19 11:04:22.96 UTC c5490cfd-6edc-4a98-9707-0156b575bc8f 2013-02-20 08:09:23.860 UTC 68a058c3-5c4b-4865-b815-3260ed9f5916 2013-12-12 14:34:40.607 UTC 03d8d882-866c-4a86-85f1-1c0a266fcfa1 2013-02-19 17:17:37.373 UTC a9fdc15c-6365-4da6-aac9-d96a9fa5b057 2013-12-11 21:50:22.587 UTC 2e37b2d4-2a11-43d7-ae86-2855f889a867 2013-06-04 10:26:47.375 UTC 45b88450-41d3-4f07-a197-0e1abc9bc1fb 2013-12-11 21:13:20.343 UTC c4e999ed-e2b1-4675-8acf-7767047c1d92 2013-12-13 12:04:03.657 UTC 6e506682-948f-4afd-825e-11210323a1d3 2013-06-06 14:50:47.515 UTC 0a9f163f-c9f6-482e-9e48-76b1971e6520 2013-02-20 12:54:19.239 UTC ebc03555-ecd5-4ce6-8391-0cbe5bf94c5f 2013-03-28 09:58:52.51 UTC 86107798-e82c-43b5-80d9-401668bb989f 2013-12-17 15:05:06.214 UTC 3f123033-68a0-4686-b89c-00586f7bcbdf 2014-04-09 12:32:33.101 UTC 5e983db4-8286-4fa1-8f6f-697d985aa3a4 2013-06-14 15:57:51.283 UTC c3075c76-212c-4c2d-98d1-e166ae1af6f9 2013-12-04 11:51:43.79 UTC b80541d1-48a8-4314-9512-98cb5fe1c276 2013-02-20 12:52:49.895 UTC 87a3fc88-51f3-435f-959f-b90c8bd55119 2013-05-17 12:40:02.751 UTC 3fe95ac3-fe41-4758-b4ea-03ecd83a123a 2013-05-16 13:07:21.5 UTC 9ffa91a8-761f-406c-8b88-076ee75eea27 2013-05-16 12:51:08.738 UTC 7a72c654-5ebe-414b-929f-71b3ca9abc15 2013-12-04 17:03:39.577 UTC 8016dd82-b2d6-4028-bd51-d01dd6bd9c93 2013-12-12 12:15:24.576 UTC Bayesian Phylogenetic Inference: Select Model For Me - 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