--- EXPERIMENT NOTES

### Obtaining branch lengths and nucleotide substitution biases under the nucleotide GTR model
* Log(L) = -10384.78, AIC-c = 20935.83 (83 estimated parameters)
* Tree length (expected substitutions/site) for partition 1 :    2.100

### Computing the phylogenetic likelihood function on the grid 
* Determining appropriate tree scaling based on the best score from a  20 x 20 rate grid
* Best scaling achieved for 
	* synonymous rate =  2.815
	* non-synonymous rate =  0.500
* Computing conditional site likelihoods on a 20 x 20 rate grid

### Running an iterative zeroth order variational Bayes procedure to estimate the posterior mean of rate weights
* Using the following settings
	* Dirichlet alpha  : 0.5

### Tabulating site-level results
|     Codon      |   Partition    |     alpha      |      beta      |Posterior prob for positive selection|
|:--------------:|:--------------:|:--------------:|:--------------:|:-----------------------------------:|
|       26       |       1        |        0.361   |        6.902   |       Pos. posterior = 0.9998       |
|       27       |       1        |        0.733   |        2.625   |       Pos. posterior = 0.9267       |
|       57       |       1        |        0.813   |        3.112   |       Pos. posterior = 0.9843       |
|       59       |       1        |        0.558   |        7.112   |       Pos. posterior = 0.9983       |
|      108       |       1        |        0.624   |        2.470   |       Pos. posterior = 0.9635       |
|      113       |       1        |        0.856   |        2.516   |       Pos. posterior = 0.9184       |
|      152       |       1        |        0.437   |        2.559   |       Pos. posterior = 0.9862       |
|      220       |       1        |        0.680   |        2.112   |       Pos. posterior = 0.9136       |
|      307       |       1        |        0.762   |        2.899   |       Pos. posterior = 0.9833       |
----
## FUBAR inferred 9 sites subject to diversifying positive selection at posterior probability >= 0.9
Of these,  0.33 are expected to be false positives (95% confidence interval of 0-2 )




 --- EXPERIMENT PROPERTIES

#Wed Jul 03 21:31:22 GMT 2019
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/opt/mrbayes_3.2.2/src
tcoffee.dir=
tcoffee.minScore=3
input.fasta=
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/data/results/aves_gene2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/results/aves_gene2/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 /data/results/aves_gene2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -9378.32         -9420.47
2      -9378.95         -9426.51
--------------------------------------
TOTAL    -9378.59         -9425.82
--------------------------------------


Model parameter summaries over the runs sampled in files
"/data/results/aves_gene2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/results/aves_gene2/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 "/data/results/aves_gene2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         4.342772    0.059347    3.884258    4.821215    4.334906   1116.27   1203.87    1.000
r(A<->C){all}   0.087400    0.000096    0.067818    0.105748    0.086934    703.43    764.45    1.000
r(A<->G){all}   0.294398    0.000447    0.255065    0.336381    0.293725    372.63    378.47    1.001
r(A<->T){all}   0.054862    0.000054    0.041109    0.069441    0.054418    576.77    623.01    1.001
r(C<->G){all}   0.126789    0.000125    0.104369    0.148212    0.126783    597.26    735.61    1.001
r(C<->T){all}   0.390366    0.000564    0.343100    0.434567    0.390455    374.12    419.38    1.001
r(G<->T){all}   0.046184    0.000042    0.033478    0.058814    0.046153    838.76    943.14    1.000
pi(A){all}      0.248265    0.000140    0.223990    0.270860    0.248338    621.69    655.76    1.000
pi(C){all}      0.215441    0.000127    0.194238    0.238030    0.215529    476.01    550.34    1.002
pi(G){all}      0.306492    0.000167    0.282177    0.332303    0.306500    387.00    511.85    1.000
pi(T){all}      0.229802    0.000153    0.205392    0.252891    0.229722    501.05    533.04    1.000
alpha{1,2}      0.246722    0.000361    0.210856    0.283850    0.245900   1247.12   1297.16    1.000
alpha{3}        1.250751    0.025833    0.947296    1.571949    1.237926   1244.46   1308.40    1.003
pinvar{all}     0.052702    0.000821    0.000065    0.102440    0.050291   1094.45   1182.79    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	-8239.045331
Model 2: PositiveSelection	-8230.564022
Model 0: one-ratio	-8496.784809
Model 3: discrete	-8191.362382
Model 7: beta	-8208.886747
Model 8: beta&w>1	-8189.27967


Model 0 vs 1	515.4789560000027

Model 2 vs 1	16.962617999997747

Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: Anas platyrhynchos (mallard) Anatidae XP 005021301.1)

            Pr(w>1)     post mean +- SE for w

     5 G      0.998**       2.468
    27 G      0.546         1.803
    29 G      0.991**       2.458
    33 P      0.638         1.939

Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: Anas platyrhynchos (mallard) Anatidae XP 005021301.1)

            Pr(w>1)     post mean +- SE for w

     5 G      0.998**       2.493 +- 0.285
    26 P      0.529         1.775 +- 0.751
    27 G      0.713         2.056 +- 0.697
    29 G      0.994**       2.488 +- 0.297
    33 P      0.782         2.161 +- 0.648


Model 8 vs 7	39.214154000001145

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: Anas platyrhynchos (mallard) Anatidae XP 005021301.1)

            Pr(w>1)     post mean +- SE for w

     5 G      1.000**       1.507
    18 G      0.932         1.441
    26 P      0.994**       1.501
    27 G      0.998**       1.505
    28 S      0.865         1.375
    29 G      1.000**       1.507
    33 P      0.998**       1.506
    66 Q      0.859         1.370
    71 A      0.880         1.390
    72 H      0.849         1.360
    78 P      0.561         1.069
   110 N      0.992**       1.500
   168 V      0.600         1.118
   170 K      0.598         1.115
   256 I      0.986*        1.494

Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: Anas platyrhynchos (mallard) Anatidae XP 005021301.1)

            Pr(w>1)     post mean +- SE for w

     5 G      0.999**       1.510 +- 0.107
    18 G      0.740         1.314 +- 0.324
    26 P      0.944         1.471 +- 0.186
    27 G      0.968*        1.490 +- 0.155
    28 S      0.664         1.250 +- 0.365
    29 G      0.998**       1.510 +- 0.108
    33 P      0.973*        1.493 +- 0.148
    66 Q      0.692         1.266 +- 0.369
    71 A      0.665         1.254 +- 0.358
    72 H      0.642         1.232 +- 0.372
   110 N      0.928         1.459 +- 0.197
   256 I      0.885         1.426 +- 0.229

>C1
MDPPGGDWTQAPRWDEKEGALLCVDIPGRRACRWSPGSGQLQAVPLDAPV
SSVALRKSGGYVVTLGTRFAALNWKEQQVTTIAHVDKDKPNNRFNDGKVD
PAGRYFAGTMAEEIRPAVLERNQGSLYTLCPDLSVVKHFDRVDISNGLDW
SLDHKTFFYIDSLSYSVDAFDYDIQTGKIDNRRSVYKLEKEESIPDGMCI
DTEGKLWVACYDGGRVIRLDPETGKRIQTVKLPVDKTTSCCFGGKDYSEM
YVTSARDGMDKEWLSRQPQAGGIFKITGLGVKGIPPYAFAGooooooooo
oooooooooooooooooo
>C2
MSSVKIECIANEGSRIGESPVWDEKESALLFVDITGRKVCRWSSVTKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEKLVTTIAHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDFAVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSARDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C3
MASVKIECVANEGYRIGESPVWDEKESALLYVDITGRKVCRWSSLSQRVQ
AVAVDAPVSSVALRKSGDYVITLGTRFAALKWKEELVTTLTHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGALYTLVVKHFDQVDISNG
LDWSLDHKTFYYIDSLSYSVDAFDYDVQTGKIGNRRNVYKLEKEENIPDG
MCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCFGGKDY
SEMYVTSASDGMDEEWLSRQPQAGGIFKITGLGVKGVPPYPFAGoooooo
oooooooooooooooooo
>C4
MSSIKIECVAKEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTKQVQ
TISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGEDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C5
MSSVKIECVANEGCRIGESPVWDEKESALLYVDITGRKVCRWSPATTRVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITQVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIQPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C6
MSSIKIECVANEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVSKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPHPFAGo
oooooooooooooooooo
>C7
MSSVKIECVASEGCRIGESPVWDEKESALVFVDITGRKVCRWSPVTKQVQ
AIAVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITQADKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDHSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSMYKLEKEE
SIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKDWLSRQPQAGGIFKITGLGVKGVAPYPFAGo
oooooooooooooooooo
>C8
MSSVKIECVTSEGFRLGESPVWDEKEGALLCVDITGRKVCRWSPATKQVQ
TVPVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLCSDLSVLKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGLFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C9
MSSIKIECVTKDGCRIGESPVWDEKESALLFVDITGRKVCRWSSVTKQVQ
AIPVDAPVSSIAHRKSGDYVITLGTRFAGLKWKEQQVTIITEIDKDKPNN
RFNDGKVDPAGRYFAGTMAEETRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIDNRRSVYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKSLKRVDCNPLDKTTSCC
FGGKDYSEMYVTSASDGMDEEWLSRQPQAGRIFKITGLGVKGIPPYPFAG
oooooooooooooooooo
>C10
MSSVKIECIASEGYGIGESPVWDAKESALLYVDITGRKVCRWSSVTKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALNWKEQLVTTIAHVDKDKSNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFTDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVLRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASVGMDKEWLSRQPQAGGVFKITGLGVKGVPPHPFAGo
oooooooooooooooooo
>C11
MSSVKIECVASEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDEDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSMYKLEKEE
SIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C12
MSSVKVECVAREGSRIGESPVWDEKENALLFVDIPAGKVCRWSAHTQRVH
AVPVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAQIDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFPDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGANCNRRSIYRLE
KEESIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTS
CCFGGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGIPPYPF
AGoooooooooooooooo
>C13
MSSVKIECIASEGYRIGESPVWDERESALLCVDITGRKVCRWSSLTKQVQ
AIAVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYELQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGRRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKDWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C14
MSSVKIECIASEGYGIGESPVWDEKEGALLCVDIAGRKVCRWSSLTGQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAHVEKDKPNN
RFNDGKVDPAGRYFAGTMAEEVRPAVLERHQGSLYTLFSDFSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDIQTGKIANRRSVYRPEKEE
SIPDGMCVDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASYGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C15
MSSIKIECVASEGYRIGESPVWDEKERALLCVDITGKKVCRWSSLTQQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQQVTTITQIDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDHSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGQDYSEMYVTSARDGMDKEWLARQPQAGGIFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C16
MSSVRIECVAKEGCRIAESPVWDEKEGALLYVDITGRKVCRWSPVTRQVQ
AIPVDAPVSSVALRKSGDYVITLGTRFAALKWKEELVTTITQVDKDKANT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFPDLSVVRHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMSIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGNDYSEMYVTTATDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C17
MSSVKIECIGSDRYRLGESPVWDEKQNSLLYVDITGRKVCRWDAASGQVQ
AVSVDAPVSSVALRKSGDYVITLGTRFAALKWKEQSVTTIAQVDRDKANN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLCPDHSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSFSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRIQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDREWLSRQPQAGGVFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C18
MSSIKIECIGSEGNRLGESPVWDEKESALLYVDITGRKVCRWSSVTNQVQ
AISVDAPVSSVALRKSGDYIITLGTRFAALKWKEQQVTTIEHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSNLSVVKHFNQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEGLSRQPQAGRVFKITGLGVKGVPPYPFVGo
oooooooooooooooooo
>C19
MLMLALCLTLLEVFEALQQGEQKRARHAEGPGFLNKQGNAAGAVEKDARR
WKLGPRPSKRLNHSKAARKNQPFDAPVSSVALRKSGDYVITLGTRFAALK
WEEQLVTTITHVDKDKPNNRFNDGKVDPAGRYFAGTMAEEIRPAVLERRQ
GSLYTLFSDLSVVKHFNQVDISNGLDWSLDHKTFFYIDSLSYSVDAFDYD
LQTGKIGNRRSIYKLEKEESIPDGMCIDTEGKLWVACYDGGRVIRLDPET
GKRLQTVKLPVDKTTSCCFGGKDYSEMYVTSARDGMDKEWLSRQPQAGGI
FKITGLGVKGVPPYPFAG
>C20
MSSIKIECVASEGYGIGESPVWDEKEDALLCVDIAGGLLWNPLFHFTLFL
DAPVSSVALRKSGDYVITLGTRFAALKWEEQLVTTITHVDKDKPNNRFND
GKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLFSDLSVVKHFNQVDISN
GLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEESIPD
GMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCFGGKD
YSEMYVTSARDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGooooo
oooooooooooooooooo
>C21
MSSVRIECVAKEGCRIGESPVWDEKEGALLYVDITGRKVCRWSPVTGQTQ
AIPVDAPVSSVALRQSGDYVITLGTRFAALKWKEQLVTSITQVDKDKVNT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFPDLSVVKHFDQV
DISNGLDWSLDHRTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C22
MSSIRIECVAKEGYRIGESPVWDEKESALLGRKVCRWSSVTQQVQAISVD
APVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNNRFNDG
KVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQVDISNG
LDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEESIPDG
MCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCFGGKDY
SEMYVTSASDGMDKDWLSRQPQAGGVFKITGLGVKGVPPYPFAGoooooo
oooooooooooooooooo
>C23
MSSVKIECVGSDRYRLGESPVWDEKENSLLCVDITGRKVCRWDAASGQVQ
AVSVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAQVDRDKANN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLCPDHSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSVYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRIQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDREWLSRQPQAGGVFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C24
MSSIKIECIASEGYRIGESPVWDEKESALLCVDITGRKVCRWNSVSNQVQ
TISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDVQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQSVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C25
MSSVKIECVANEGCRIGESPVWDEKESALLFVDITGRKVCRWSPAAKQAQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITQVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIQPAVLERHQGSLYTLFPDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C26
MSSVKIECVANEGCRIGESPVWDEKESALLFVDITGRKVCRWSPAAKQAQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITQVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIQPAVLERHQGSLYTLFPDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDIQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C27
MSSVGIECVAREGCRIGESPVWDEKEGALLFVDITGRKVCRWSPVTRQAQ
AIAVDAPVSSVALRKSGDYVITLGTRFAALKWKEGLVTTITQVDKDKANT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLLPDISVVKHFDQV
DISNGLDWSLDHRTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMFVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVAPYPFAGo
oooooooooooooooooo
>C28
MSSVRIECVANEGYRIGESPVWDEKEDALLYVDISGRKVCRWSPVTRQAQ
AIPVDAPVSSVALRKSGDYVITLGTKFAALKWKEEQVTTITQVDKDKPNN
RFNDGKVDPAGRYFAGTMAEETRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
NIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C29
MSSVKIECIGSDRYRLGESPVWDEKENSLLYVDITGRKVCRWDAASGQVQ
AVSVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAQVDRDKAKN
RFNDGKVDPAGRYFAGTMAEEIRPAVLEPRQGSLYTLCPDHSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
NIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRIQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDREWLSKQPQAGGVFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C30
MSAVKIECVASEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTKQVQ
AISVDAPVSSVALRKSGGYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYSLLSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPFPFAGo
oooooooooooooooooo
>C31
MSSVKVECVTSEGCRIGESPVWDEKESALLYVDISGRKVCRWSSLTQQVQ
DVSVDAPVSSVALRRSGDYVITLGTRFAALKWKEQLITTIAHVDKDKANN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKQFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMFVTSASDGMDKEWLSRQPQAGRIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C32
MSSIKIECIADESYRIGESPVWDEKEGVLLCVDITGRKVCRWSPVTKQVQ
AISVDAPVSSVALRKSGDYVVTLGTRFAALKWKEQLVTTIAHVDKDKTNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLNSDLSVVKHFDKV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDIQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C33
MSSVKIECVASEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTKQIQ
AISVDAPVSSVALRKSGGYVITLGTRFAALKWNEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYSLHSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIDNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C34
MSSVQIECVAREGCRIGESPVWDEKESALLCVDITGRKVCRWSWVTKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAQVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSVYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C35
MSSVKIECVGSERYRLGESPVWDEKEGSLLCVDITGRKVCRWDSASGQVQ
AVSVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAQVDRDKASN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLCPDHSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYNLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYNGGRVIRLDPETGKRIQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDREWLSRQPQAGGVFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C36
MASVKIECVASKGYGIGESPVWDEKESALLCVDITGRKVCRWSAVTKQVE
AIAVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTIAHVDKDKPNN
RFNDGKVDPAGRYFAGMLQAVLCDCSAWGREGSGFYLFPDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDIQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSARDGMDEEWLSRQPQAGGLFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C37
MSSVRIECVAKEGYRIGESPVWDEKEGALLCVDITGRKVCRWSPLTGETR
AIPVDAPVSSVALRKSGDYVITLGTRFAALKWKEELVTTITQVDKDKANT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLLPDLSVVKHFDQV
DISNGLDWSLDHRIFFYIDSLSYSVDAFDYDLQTGKIGNRRNIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSWQPQAGGIFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C38
MSSVKIECVANEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTQRVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKNKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLARQPQAGGVFKITGLGVKGVPPNPFAGo
oooooooooooooooooo
>C39
MSSIKIECVANEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTGQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKGWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C40
MSSIKIECITKENNEIGESPVWDEKESSLLYVDITGKKVCRWSSVTKQVQ
AISVGNLVGSVALRKSGDYVITLGTTFAALKWKEQVVTTITQVDNGKPNT
RFNDGKVDPAGRYFAGTMPDEVHPHMMERKQGALYTLFSDHSVVKHFDQV
DVSNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKISNRRSVYKLEKEE
NIPDGMCIDTEGKLWVACYNGGRVLRLDPETGKRLQTLKLPVDKTTSCCF
GGKDYSEMYVTSASVEMDKEYLARQPQAGRIFKITGLGVKGVPPNPFAGo
oooooooooooooooooo
>C41
MSSVRIECVAEEGYGIGESPVWDEKEGALLCVDITGRKVCRWSPLTGETQ
AMPVDAPVSSVALRKSGDYVITLGTRFAALKWKEELVTTITQVDKDKANT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLLPDLSVVKHFDQV
DISNGLDWSLDHRIFFYVDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C42
MSSVKIECVAKEGYRIGESPVWDEKESALLCVDITGRKVCRWSSVTKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKEQLVTTLTHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFSDLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYRLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGEDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C43
MASVSIECVAREGCRIGESPVWDQREGALLFVDITGRKVCRWSPLTRQTQ
AIAVDAPVSSVALRKSEDYVITLGTRFAALKWKEELVTTITQVDKDKANT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLFPDLSVVKHFDQV
DISNGLDWSLDHRTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMFVTSASDGMDKEWLSRQPEAGGIFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C44
MSSVKIECVASENYKIGESPVWDEKENSLLYVDITGKKVCKWNSLTKQVQ
AISVDAPVSSVALRKSGDYVITLGTRFAALKWKDQLVTTITHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGALYTLLADLSVVKHFDQV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLHTGKIGNRRSIYKMEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRIQTVKLPVDKTTSCCF
GGKDYSEMYVTSASEGMDKDWLSRQPQAGGVFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C45
MSSVRIECVAKEGCRIGESPVWDEKQGALLYVDITGRKVCRWSPVTRQTQ
AIPVDAPVSSVALRQSGDYVITLGTRFAALKWKEELVTTITQVDKDKANN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLFPDLSVVKHFDQV
DISNGLDWSLDHRTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDAETGKRLQTVKLPVDKTTSCCF
GGNDYSEMYVTSASDGMDKEWLSRQPQAGGVFKITGLGVKGVPPYPFAGo
oooooooooooooooooo
>C46
MSSVSIECVAREGCRIGESPVWDEKEGALLFVDITGRKVCRWSPVTRQAQ
AIAVDAPVSSVALRKSGDYVITLGTRFAALKWKEGLVTTITQVDKDKANT
RFNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLLPDLSVVKHFDQV
DISNGLDWSLDHRTFFYIDSLSYSVDAFDYDLQTGKIGNRRSIYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMFVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVAPYPFAGo
oooooooooooooooooo
>C47
MASIKIECVAKENCKIGESPVWDAKENSLLYVDITGRKVCKWSSLTQQVQ
AIPVDAPVSSLALRKSGDYVITLGTRFASLKWKDQVVTTIAHVDKDKPNN
RFNDGKVDPAGRYFAGTMAEEIRPAVLERHQGSLYTLHADHSVVKHFDRV
DISNGLDWSLDHKTFFYIDSLSYSVDAFDYDLQTGKIGNRRSMYKLEKEE
SIPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCF
GGKDYSEMYVTSASEGMDKDWLSRQPQAGGVFKITGLGVKGIPPYPFAGo
oooooooooooooooooo
>C48
MSSVSIECVAEGCRIGESPVWDDREGALLYVDITGRKVCRWSPVTRQAQA
IALDAPVSSVALRQSGGYVITLGTRFAALKWKEELVTTIAQVDKDKANTR
FNDGKVDPAGRYFAGTMAEEIRPAVLERRQGSLYTLLPDLSVVKHFGQVD
ISNGLDWSLDHRTFFYIDSLSYSVDAFDYDLQTGKIGNRRNIYKLEKEES
IPDGMCIDTEGKLWVACYDGGRVIRLDPETGKRLQTVKLPVDKTTSCCFG
GKDYSEMFVTSASDGMDKEWLSRQPQAGGIFKITGLGVKGVPPYPFAGoo
oooooooooooooooooo
CLUSTAL FORMAT for T-COFFEE Version_10.00.r1613 [http://www.tcoffee.org] [MODE:  ], CPU=0.00 sec, SCORE=100, Nseq=48, Len=352 

C1              --------MD------------PPGGDWTQAPRWDEKEGALLCVDIPGRR
C2              MSSVKIECIA------------NEGSRIGESPVWDEKESALLFVDITGRK
C3              MASVKIECVA------------NEGYRIGESPVWDEKESALLYVDITGRK
C4              MSSIKIECVA------------KEGYRIGESPVWDEKESALLCVDITGRK
C5              MSSVKIECVA------------NEGCRIGESPVWDEKESALLYVDITGRK
C6              MSSIKIECVA------------NEGYRIGESPVWDEKESALLCVDITGRK
C7              MSSVKIECVA------------SEGCRIGESPVWDEKESALVFVDITGRK
C8              MSSVKIECVT------------SEGFRLGESPVWDEKEGALLCVDITGRK
C9              MSSIKIECVT------------KDGCRIGESPVWDEKESALLFVDITGRK
C10             MSSVKIECIA------------SEGYGIGESPVWDAKESALLYVDITGRK
C11             MSSVKIECVA------------SEGYRIGESPVWDEKESALLCVDITGRK
C12             MSSVKVECVA------------REGSRIGESPVWDEKENALLFVDIPAGK
C13             MSSVKIECIA------------SEGYRIGESPVWDERESALLCVDITGRK
C14             MSSVKIECIA------------SEGYGIGESPVWDEKEGALLCVDIAGRK
C15             MSSIKIECVA------------SEGYRIGESPVWDEKERALLCVDITGKK
C16             MSSVR