hello everyone , i am beginner in Bioinformatics ,
as i am working on gene name msp ,i m not getting how to interpret the result like it showing branch length and scale bar of 0.04 what does scale 0.04 indicate
i have used Bayes software , and calculated branchlength with bayesian posterior distrubution. and what does scalre
plz fined attached files
Hope somebody help me out in this matter , all gens are of same organism . i need to fine variation
Hi,
The branch length = number of changes/site/some unit of time.
I agree with Zev, you need to do something to improve the resolution of that tree. It looks like most variants have no changes? Is this correct?
hey zev i have run same sequences upto 1e6 generations again . and it shows like
Read a total of 20002 trees in 2 files (sampling 15002 of them) (Each file contained 10001 trees of which 7501 were sampled)
Summary statistics for partitions with frequency >= 0.10 in at least one run: Average standard deviation of split frequencies = 0.003233 Maximum standard deviation of split frequencies = 0.007919 Average PSRF for parameter values ( excluding NA and >10.0 ) = 1.000 Maximum PSRF for parameter values = 1.001 Using relative burnin ('relburnin=yes'), discarding the first 25 % of sampled trees
nope all sequences are different of same gene not identical to eachother but yep, its belongs to same species , and i need to find genetic divergence .wats ur opinion ?
zev it is a diverse sequence ..and wat amount of burnin samples i required for perfect bayesian?? , how could i anlysed the result
If the branchlength is 0.2 it means you "expect" an average of 0.2 substitutions per site. So if there are 100 sites in the sequence, you expect, on average, about 2 substitutions to have occurred along that branch.
Whetting . i have used TN93 model (Tamura-Nei, 93 ). now wat i want is to learn that how should i analyze this result.. would u plz help me ? all sequences are of same gene.
I am not sure whether this is what you are asking but:
0) How long are your sequences?
1) use modeltest (or jmodeltest) to estimate which model of evolution best fits your data
3) build a phylogenetic tree using that model (I would try both MrBayes and Maximum likelihood)
As far as interpreting your result, it is hard for me to help you. I do not even know what these sequences are. In addition, given the fact that the Bayesian tree is not resolved, I would be VERY careful making any conclusions!
Exactly. If you are learning to do phylogenetic analyses these may not have been the best data to try. There are "tricks of the trade" that pop up when trying to do analyses of very closely related samples (like clinical isolates of bacteria/viruses). Working in nucleotide space, while seemingly easier, often also has its own issues that I think make it not ideal for learning on. It isn't trivial to do phylogenetics well. I'd find a tutorial resource online to go through it and learn personally.
This is a juz simple sample data ,i have retrieved it from public database to learn and anallyze phylogenetic tree.all sequences is around 1150 bp. i m trying to fing genetic divergence.
ok Than k you for your valuable suggestion.. if u dont mind .give me ur Yahoo or gmail id.. i wil send u this sample sequence data..hope u can frame it well wid bayesian and maximum liklihood
based on the NJ tree it appears that you have two main clades. However, the bayesian analysis throws a wrench in that conclusion. I would start by having a look here http://bioinf.ncl.ac.uk/molsys/data/like.pdf
1) look at your burn in. I bet you need to run way more than 1e6 runs. 2) yes at 1 position.
hey zev i have run same sequences upto 1e6 generations again . and it shows like
Read a total of 20002 trees in 2 files (sampling 15002 of them) (Each file contained 10001 trees of which 7501 were sampled)
Summary statistics for partitions with frequency >= 0.10 in at least one run: Average standard deviation of split frequencies = 0.003233 Maximum standard deviation of split frequencies = 0.007919 Average PSRF for parameter values ( excluding NA and >10.0 ) = 1.000 Maximum PSRF for parameter values = 1.001 Using relative burnin ('relburnin=yes'), discarding the first 25 % of sampled trees
with bayesian probability
with Branch length 
I believe your tree ran long enough. I wonder whether you have enough variability in your sequences. Are most of these sequences the same?
Yes. Whetting is right. It looks like you need more diverse sequences to clear up the polytomies.
nope all sequences are different of same gene not identical to eachother but yep, its belongs to same species , and i need to find genetic divergence .wats ur opinion ?
zev it is a diverse sequence ..and wat amount of burnin samples i required for perfect bayesian?? , how could i anlysed the result
Are these nt or aa sequences? Do you have more sequence data available? At this point the tree cannot be resolved. Not much more you can do...
If the branchlength is 0.2 it means you "expect" an average of 0.2 substitutions per site. So if there are 100 sites in the sequence, you expect, on average, about 2 substitutions to have occurred along that branch.
hi, its nucleotide sequence , what about this tree ?? , same all sequence i have framed with help of NJ Method
at least this tree is resolved. Are you sure you are using the correct model?
Whetting . i have used TN93 model (Tamura-Nei, 93 ). now wat i want is to learn that how should i analyze this result.. would u plz help me ? all sequences are of same gene.
I am not sure whether this is what you are asking but: 0) How long are your sequences? 1) use modeltest (or jmodeltest) to estimate which model of evolution best fits your data 3) build a phylogenetic tree using that model (I would try both MrBayes and Maximum likelihood)
As far as interpreting your result, it is hard for me to help you. I do not even know what these sequences are. In addition, given the fact that the Bayesian tree is not resolved, I would be VERY careful making any conclusions!
Exactly. If you are learning to do phylogenetic analyses these may not have been the best data to try. There are "tricks of the trade" that pop up when trying to do analyses of very closely related samples (like clinical isolates of bacteria/viruses). Working in nucleotide space, while seemingly easier, often also has its own issues that I think make it not ideal for learning on. It isn't trivial to do phylogenetics well. I'd find a tutorial resource online to go through it and learn personally.
This is a juz simple sample data ,i have retrieved it from public database to learn and anallyze phylogenetic tree.all sequences is around 1150 bp. i m trying to fing genetic divergence.
ok Than k you for your valuable suggestion.. if u dont mind .give me ur Yahoo or gmail id.. i wil send u this sample sequence data..hope u can frame it well wid bayesian and maximum liklihood
based on the NJ tree it appears that you have two main clades. However, the bayesian analysis throws a wrench in that conclusion. I would start by having a look here http://bioinf.ncl.ac.uk/molsys/data/like.pdf