--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Nov 12 00:45:34 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/2/Abl-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/2/Abl-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/2/Abl-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)

(Values are saved to the file /opt/ADOPS/2/Abl-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -14935.82        -14951.49
2     -14936.37        -14953.09
--------------------------------------
TOTAL   -14936.06        -14952.58
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/2/Abl-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/2/Abl-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
Summaries are based on a total of 3002 samples from 2 runs.
Each run produced 2001 samples of which 1501 samples were included.
Parameter summaries saved to file "/opt/ADOPS/2/Abl-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.787466    0.001051    0.723095    0.849453    0.786687   1477.98   1482.74    1.000
r(A<->C){all}   0.081350    0.000066    0.065749    0.097226    0.081102   1085.96   1091.11    1.000
r(A<->G){all}   0.237455    0.000222    0.206450    0.264577    0.237114    919.23    952.55    1.000
r(A<->T){all}   0.164295    0.000241    0.133557    0.194215    0.163796    901.91    947.13    1.000
r(C<->G){all}   0.040937    0.000022    0.031787    0.050197    0.040800    986.75   1134.80    1.001
r(C<->T){all}   0.379734    0.000345    0.342372    0.414997    0.379931    748.04    778.55    1.000
r(G<->T){all}   0.096229    0.000106    0.076887    0.116455    0.095942   1124.49   1143.98    1.000
pi(A){all}      0.232558    0.000034    0.220998    0.243320    0.232601    969.00   1052.30    1.000
pi(C){all}      0.320617    0.000039    0.308509    0.332443    0.320471    996.34   1052.06    1.001
pi(G){all}      0.284757    0.000040    0.271639    0.296079    0.284628    967.66   1072.69    1.000
pi(T){all}      0.162068    0.000024    0.152608    0.171882    0.161850    929.90    996.92    1.000
alpha{1,2}      0.130354    0.000076    0.112894    0.147104    0.130179   1382.96   1414.86    1.000
alpha{3}        6.611760    1.625309    4.265224    9.180761    6.486721   1311.35   1406.18    1.000
pinvar{all}     0.378240    0.000455    0.339652    0.423048    0.377980   1209.64   1325.05    1.000
------------------------------------------------------------------------------------------------------
* Convergence diagnostic (ESS = Estimated Sample Size); min and avg values
correspond to minimal and average ESS among runs.
ESS value below 100 may indicate that the parameter is undersampled.
+ Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman
and Rubin, 1992) should approach 1.0 as runs converge.


Setting sumt conformat to Simple



 --- CODEML SUMMARY

Model 1: NearlyNeutral	-13576.935707
Model 2: PositiveSelection	-13576.935708
Model 0: one-ratio	-13704.788551
Model 3: discrete	-13568.334719
Model 7: beta	-13568.905111
Model 8: beta&w>1	-13568.541213


Model 0 vs 1	255.7056879999982

Model 2 vs 1	2.0000006770715117E-6

Model 8 vs 7	0.7277959999992163
>C1
MGAQQGKDRGAHSGGGGSGAPVSCIGLSSSPVASVSPHCISSSSGVSSAP
LGGGSTLRGSRIKSSSSGVASGSGSGGGGGGSGSGLSQRSGGHKDARCNP
TVGLNIFTEHNGTKHSSFRGHPGKYHMNLEALLQSRPLPHIPAGSTAASL
LADAAELQQHQQDSGGLGLQGSSLGGGHSSTTSVFESAHRWTSKENLLAP
GPEEDDPQLFVALYDFQAGGENQLSLKKGEQVRILSYNKSGEWCEAHSDS
GNVGWVPSNYVTPLNSLEKHSWYHGPISRNAAEYLLSSGINGSFLVRESE
SSPGQRSISLRYEGRVYHYRISEDPDGKVFVTQEAKFNTLAELVHHHSVP
HEGHGLITPLLYPAPKQNKPTVFPLSPEPDEWEICRTDIMMKHKLGGGQY
GEVYEAVWKRYGNTVAVKTLKEDTMALKDFLEEAAIMKEMKHPNLVQLIG
VCTREPPFYIITEFMSHGNLLDFLRSAGRETLDAVALLYMATQIASGMSY
LESRNYIHRDLAARNCLVGDNKLVKVADFGLARLMRDDTYTAHAGAKFPI
KWTAPEGLAYNKFSTKSDVWAFGVLLWEIATYGMSPYPAIDLTDVYHKLD
KGYRMERPPGCPPEVYDLMRQCWQWDATDRPTFKSIHHALEHMFQESSIT
EAVEKQLNANATSASSSAPSTSGVATGGGATTTTAASGCASSSSATASLS
LTPQMVKKGLPGGQALTPNAHHNDPHQQQASTPMSETGSTSTKLSTFSSQ
GKGNVQMRRTTNKQGKQAPAPPKRTSLLSSSRDSTYREEDPANARCNFID
DLSTNGIHKLKTANYFSQTLSRNFKTQIPTHHTHQIRTQQQQQQQSVQQQ
QQIVPLSVQQQAHQQQQKQQQYSIKKSSSCSSFLYDILFRGLARDINSLT
QRYDSETDPAADPDTDATGDSLEQSLSQVIAAPVTNKMQHSLHSGGGGGG
IGPRSSQQHSSFKRPTGTPVMGNRGLETRQSKRSQLHSQAPGPGPPSTQP
HHGNNGVVTSAHPITVGALDVMNVKQVVNRYGTLPKGARIGAYLDSLEDS
SEAAPALPATAPSLPPANGHATPPAARLNPKASPIPPQQMIRSNSSGGVT
MQNNAAASLNKLQRHRTTTEGTMMTFSSFRAGGSSSSPKRSASGVASGVQ
PALANLEFPPPPLDLPPPPEEFEGGPPPPPPAPESAVQAIQQHLHAQLPN
NGNISNGNGTNNNDSSHNDVSNIAPSVEEASSRFGVSLRKREPSTDSCSS
LGSPPEDLKEKLITEIKAAGKDTAPASHLANGSGIAVVDPVSLLVTELAE
SMNLPKPPPQQQQKLTNGNSTGSGFKAQLKKVEPKKMSAPMPKAEPANTI
IDFKAHLRRVDKEKEPATPAPAPATVAVANNANCNTTGTLNRKEDGSKKF
SQAMQKTEIKIDVTNSNVEADAGAAGEGDLGKRRSTDDEEQSHTEGLGSG
GQGSADMTQSLYEQKPQIQQKPAVPHKPTKLTIYATPIAKLTEPASSASS
TQISRESILELVGLLEGSLKHPVNAIAGSQWLQLSDKLNILHNSCVIFAE
NGAMPPHSKFQFRELVTRVEAQSQHLRSAGSKNVQDNERLVAEVGQSLRQ
ISNALNRooooooooooooooooooooooo
>C2
MGAQQGKDRGAHSGGGGSGAPVSCIGLSSSPVASVSPHCISSSSGVSSAP
LGGGSTLRGSRIKSSSSGVASGSGSGGGGGGSGSGLSQRSGGHKDARCNP
TVGLNIFTEHNGTKHSSFRGHPGKYHMNLEALLQSRPLPHIPAGSTAASL
LADAAELQQHQQDSGGLGLQGSSLGGGHSSTTSVFESAHRWTSKENLLAP
GPEEDDPQLFVALYDFQAGGENQLSLKKGEQVRILSYNKSGEWCEAHSDS
GNVGWVPSNYVTPLNSLEKHSWYHGPISRNAAEYLLSSGINGSFLVRESE
SSPGQRSISLRYEGRVYHYRISEDPDGKVFVTQEAKFNTLAELVHHHSVP
HEGHGLITPLLYPAPKQNKPTVFPLSPEPDEWEICRTDIMMKHKLGGGQY
GEVYEAVWKRYGNTVAVKTLKEDTMALKDFLEEAAIMKEMKHPNLVQLIG
VCTREPPFYIITEFMSHGNLLDFLRSAGRETLDAVALLYMATQIASGMSY
LESRNYIHRDLAARNCLVGDNKLVKVADFGLARLMRDDTYTAHAGAKFPI
KWTAPEGLAYNKFSTKSDVWAFGVLLWEIATYGMSPYPGIDLTDVYHKLE
KGYRMERPPGCPPEVYDLMRQCWQWDATDRPTFKSIHHALEHMFQESSIT
EAVEKQLNANATSASSSAPSTSGVATGGGATTTTAASGCASSSSATASLS
LTPQMVKKGLSGGQSLTPNAHHNDPHQQQASTPMSETGSTSTKLSTFSSQ
GKGNVQMRRTTNKQGKQAPAPPKRTSLLSSSRDSTYREEDPANARCNFID
DLSTNGIHKLKTANYFSQTLSRNFKTQIPTQHTHQIRTQQQQQQQSVQQQ
QQTVPLSVQQQPHQQQKQQQYSIKKSSSCSSFLYDILFRGLARDINSLTQ
RYDSETDPAGDPDTDATGDSLEQSLSQVIAAPATNKMQHSLHSGGGGGGI
GPRSSQQHSSFKRPTGTPVMGNRGLETRQSKRSQHHPQAPGPGPPSTQPH
HGNNGVLTSAHPITVGALEVMNVKQVVNRYGTLPKGARIGAYLDSLEDST
EAAPPLPATAPSLPPANGHATPPSARLNPKASPIPPQQMIRSNSSGGVTM
QNNAAASLNKLQRHRTTTEGTMMTFSSFRAGGSSSSPKRSASGLASGVQP
ALANLEFPPPPLDLPPPPEEFEGGPPPPPPAPESAVQAIQQHLHAQLPNN
GNISNGNGSNNNDSSHNDVSNIAPSVEEASSRFGVSLRKREPSTDSCSSL
GSPPEDLKEKLITEIKAAGKESAPASHLANGSGIAVVDPVSLLVTELAES
MNLPKSPPQQQQKLTNGNGTGSGFKAQLKKVEPKKMSAPMPKAEPASTII
DFKAHLRRVDKEKEPAAPAPAPVAVANNANCNTTGTLNRKEDSSKKFSQA
MQKTEIKIDVTNSNVEADAGATGEGDLGKRRSTDDEEQSHTEGLGSGGQG
AADMTQSLYEQKPQIQQKPAVPHKPTKLTIYATPIAKLTEPASSASSTQI
SRESILELVGLLEGSLKHPVNAIAGSQWLQLSDKLNILHNSCVIFAENGA
MPPHSKFQFRELVTRVEAQSQHLRSAGSKNVQDNERLVAEVGQSLRQISN
ALNRoooooooooooooooooooooooooo
>C3
MGAQQGKDRGAHSGGGGSGAPVSCIGLSSSPVASVSPHCISSSSGVNSAP
LGGGSTLRGSRIKSSSSGVASGSGSGGGGGSGSGLSQRSGGHKDARCNPT
VGLNIFTEHNGTKHSSFRGHPGKYHMNLEALLQSRPLPHIPAGSTAASLL
ADAAELQQHQQDSGGLGLQGSSLGGGHSSTTSVFESAHRWTSKENLLAPG
PEEDDPQLFVALYDFQAGGENQLSLKKGEQVRILSYNKSGEWCEAHSDSG
NVGWVPSNYVTPLNSLEKHSWYHGPISRNAAEYLLSSGINGSFLVRESES
SPGQRSISLRYEGRVYHYRISEDPDGKVFVTQEAKFNTLAELVHHHSVPH
EGHGLITPLLYPAPKQNKPTVFPLSPEPDEWEICRTDIMMKHKLGGGQYG
EVYEAVWKRYGNTVAVKTLKEDTMALKDFLEEAAIMKEMKHPNLVQLIGV
CTREPPFYIITEFMSHGNLLDFLRSAGRETLDAVALLYMATQIASGMSYL
ESRNYIHRDLAARNCLVGDNKLVKVADFGLARLMRDDTYTAHAGAKFPIK
WTAPEGLAYNKFSTKSDVWAFGVLLWEIATYGMSPYPGIDLTDVYHKLEK
GYRMERPPGCPPEVYDLMRQCWQWDATDRPTFKSIHHALEHMFQESSITE
AVEKQLNANATSASSSAPSTSGVATGGGATTTTAASGCASSSSATASLSL
TPQMVKKGLPGGQSLTPNAHHNDSHQQQASTPMSETGSTSTKLSTFSSQG
KGNVQMRRTTNKQGKQAPAPPKRTSLLSSSRDSTYREEDPATARCNFIDD
LSTNGIHKLKTANYFSQTLSRNFKTQIPTHHTHQIRTQLQQQQSVQQQTV
PLPVQQQQPQHQKQKQQQYSIKKSSSCSSFLYDILFRGLARDINSLTQRY
DSETDPAADPDTDATGDSLEQSLSQVIAAPATNKMQHSLHSGGGGGGIGP
RSSQQHSSFKRPTGTPVMGNRGLETRQSKRSQHHPLAPGPGPPATQPHHG
NNGVVASAHPITVGALEVMNVKQVVNRYGTLPKVARIGAYLDSLEDSTEA
APALPATAPALPPANGHATPPAARINPKASPIPPQQMIRSNSSGGVTMQN
NAAASLNKLQRHRTTTEGTMMTFSSFRAGGSSSSPKRNATGAASGVQPAL
ANLEFPPPPLDLPPPPEEFEGGPPPPPPAPESAVQAIQQHLHAQLPNNGN
ISNGNGTNNNDSSHNDVSNTAPSVEEASSRFGVSLRKREPSTDSCSSLGS
PPEDLKEKLITEIKAAGKDSAPASQLANGSGIAVVDPVSLLVTELAESMN
LPKPPPQQQKLTNGNGTGSGFKAQLKKVEPKKMSAPIAKAEPANTIIDFK
AHLRRVDKEKEPAAPAPAPVAVTNNANCNTTGTLNRKEDSSKKFSQAMQK
TEIKIDVTNSNVEADAGAAGEGDLGKRRSTDDEEQSHSDGLGSGGQGAAD
MTQSLYEQKPQIQQKPAVPHKPTKLTIYATPIAKLAEPASSASSTQISRD
SILELVGLLEGSLKHPVNAIAGSQWLQLSDKLNILHNSCVIFAENGAMPP
HSKFQFRELVTRVEAQSQHLRSAGSKNVQDNERLVAEVGQSLRQISNALN
Rooooooooooooooooooooooooooooo
>C4
MGAQQGKDRGGHSGGGGSGAPVSCIGLSSSPVASVSPHCISSSSGVSSAP
LGGGSTLRGSRIKSSSSGVASGSGSGGGGGGSGSGLSQRSGGHKDARCNP
TVGLNIFTEHNGTKHSSFRGHPGKYHMNLEALLQSRPLPHIPAGSTAASL
LADAAELQQHQQDSSGLGLQGSSLGGGHSSTTSVFESAHRWTSKENLLAP
GPEEDDPQLFVALYDFQAGGENQLSLKKGEQVRILSYNKSGEWCEAHSDS
GNVGWVPSNYVTPLNSLEKHSWYHGPISRNAAEYLLSSGINGSFLVRESE
SSPGQRSISLRYEGRVYHYRISEDPDGKVFVTQEAKFNTLAELVHHHSVP
HEGHGLITPLLYPAPKQNKPTVFPLSPEPDEWEICRTDIMMKHKLGGGQY
GEVYEAVWKRYGNTVAVKTLKEDTMALKDFLEEAAIMKEMKHPNLVQLIG
VCTREPPFYIITEFMSHGNLLDFLRSAGRETLDAVALLYMATQIASGMSY
LESRNYIHRDLAARNCLVGDNKLVKVADFGLARLMRDDTYTAHAGAKFPI
KWTAPEGLAYNKFSTKSDVWAFGVLLWEIATYGMSPYPGIDLTDVYHKLE
KGYRMERPPGCPPEVYDLMRQCWQWDATDRPTFKSIHHALEHM