Dear Sarah,

Hi, I'm covering for Sergei this week while he's abroad.

Regarding the batch file dNdSRateAnalysis.bf:
• HyPhy attempts to fit one of several available codon substitution rate models to your data.  The parameters of the codon rate matrix are estimated as either global variables, or local to each branch of your tree. 
• By selecting "Run all available models" at the "Rate Variation Options" window, HyPhy will iterate through all five possible models of rate variation across sites (starting at line 530) so that you can compare their likelihoods.
• The option to select between default or randomized initial values for the rate distribution parameters (line 407) actually appears to be an unused option -- possibly left-over from earlier versions of the batch file.
• Given the number of sequences that you are trying to fit, and the complexity of the model that you're fitting, the amount of time elapsed doesn't seem unreasonable for your computer.  (There's a lot of parameters being fit to a lot of data!)  You might want to keep an eye on the messages.log file for error messages, just to be sure that nothing's gone awry.

I can't find the batch file dNdSpost.bf anywhere on my computer!  Is this from an earlier version of HyPhy?

As far as I can tell, post_sns.bf is a post-processing batch file that generates and displays trees based specifically on either synonymous or non-synonymous rates of substitution that were estimated from fitting a codon model.  In other words, one would use this after executing something like dNdSRateAnalysis.bf.

The step-by-step procedure for fitting a codon model to a codon partition is, as you say, in the documentation.  This is basically equivalent to dNdSRateAnalysis.bf, except executed through the HyPhy GUI.

Under the "Codon Selection" submenu, there is a batch file dNdSBivariateRateAnalysis.bf which applies the site-specific estimation of synonymous substitution rates described in Kosakovsky Pond and Muse (1995) MBE 22(12):2375.

Under the "Positive Selection" submenu, the batch file QuickSelectionDetection.bf applies methods described in Kosakovsky Pond et al. (2005) MBE 22(5): 1208.  This first fits a codon model to the data in a similar manner to dNdSRateAnalysis.bf before reconstructing ancestral states for inferring the number of NS and S substitutions per site.

Okay!  I'm sure Sergei could provide a much more informed overview, but I hope this helps you out a bit.  Lemme know if you need more detailed explanations on stuff.

- Art.

Regarding the difference between dNdSRateAnalysis.bf and dNdSBivariateRateAnalysis.bf, one comment that concerns me is

Quote:

(from Multimedia File Viewing and Clickable Links are available for Registered Members only!!  You need to Login)

This suggests there are major differences between the two implementations, but I can't find where they are described.

Thanks again,
Sarah

Dear Sarah,

Phew! That's a lot of questions...I thought that I would chip in too...

Quote:


We had a paper looking at selection varying across both branches and across sites Multimedia File Viewing and Clickable Links are available for Registered Members only!!  You need to Login, although unlike the 'branch-sites' sorts of models, we assumed that the distributions across branches and sites were independent. Is this what you want?

MFPositiveSelection is an old batch file used to estimate dN/dS jointly across multiple datasets (like HIV sequences from different infected individuals). The different branch batch files really depend on which branches you want to look at; in the tips of the tree, an isolated branch, a subtree, or some more complicated setup.

Best
Simon

Hi, Art & Simon,

First, your GA approach is impressive and ideally what I would do, but I don't have the skills/time at the moment. If these preliminary analyses are suggestive, I would like to pursue it. (I assume it's not implemented anywhere in HyPhy.)

TestBranchDNDS.bf could be bad here: I don't want to specify branches a priori because I expect a lot of variation in selection across the tree. I was hoping that dNdSBivariateRateAnalysis.bf (or the last model in dNdSRateAnalysis.bf) would provide a way around this problem. Lineage Dual is obviously not as nice as pulling from discrete categories of omegas, but it's a start... though I'm not sure if it's what I'm running now... or if anything's running... or exactly what form the output will take. It would definitely be good to run independent branch and site models and compare them (I suspect I'll need both branch and site variation). Will later try the free ratio model in PAML.

I'll test NucModelCompare.bf and CodonModelCompare.bf once dNdSBivariateRateAnalysis.bf has finished.

Thanks again for your help; I wish I weren't so new to this. Rather than peppering you with more questions, I will focus on understanding the batch code and linking the literature to the options in the software.

Thanks again,
Sarah

Dear Sarah,

One more thing; you can fit models allowing different dN/dS classes for each branch in HyPhy by specifying 'local' models rather than 'global' models. This is easy to do in the graphical user interface - if the model you want isn't there, you can make your own up (see Multimedia File Viewing and Clickable Links are available for Registered Members only!!  You need to Login). You can fit a 'local' model, with separate dN/dS categories per branch in much the same way as described in one of Sergei's excellent tutorials (Multimedia File Viewing and Clickable Links are available for Registered Members only!!  You need to Login).

Have fun learning about HyPhy!
Simon

Dear Sarah,

GA-Branch is not a branch-site method, it looks for signatures of alignment-wide selection at the level of a single branch. You can include site-by-site rate variation as well, but it will be independent of the branch-by-branch rate variation (i.e. a 'slow' site will be slow in all branches of the tree). I am not sure why your analysis died - would you please try it again and let me know if the problem persists?

I did implement a PAML style Branch-Site model upon request (search the message boards way back and you should find the reference), in case you want to try that.

There is no reference to dNdSBivariateRateAnalysis.bf because it is an unpublished (yet) method - it is very similar in spirit to dNdSRateAnalysis.bf (which is described in the paper we wrote with Spencer Muse in MBE), except that dN and dS are no longer assumed to come from independent distributions, but rather from a general discrete bivariate distribution. The key difference is that dN and dS can (and will in general) co-vary in the dNdSBivariateRateAnalysis.bf analysis. Another thing about this analysis is that selection strength does not vary along the tree.

Based on what you want to do (compare alignment-wide dN/dS along branches between different data sets), a GA-branch style approach seems ideal. It will

(a). Free you from having to assign branches to rate classes a priori
(b). Avoid model overfitting as the free ratio model will almost certainly do (hence leading to very large variances in parameter estimates)
(c). Provide natural confidence intervals for dN/dS over branches averaged over models.

Let me know if I can be of further assistance.

Sergei

Dear Sarah,

Let me know if you run into problems running jobs locally.

Indeed, one could use FEL on the same tree to look for codons under selection post-hoc (i.e. use the GA to find putatively selected branches, then use FEL to test for selection on those branches), but there are some statistical issues of bias here, whereby one uses the same data to first formulate a hypothesis (i.e. find branches under selection) and then test for evidence for/against it using the same data. It's permissible for exploratory data analysis, though.

Alternatively, you could use SLAC/FEL to infer substitution histories for each codon, and then correlate them with the branches under selection globally. However, this is also mostly an exploratory analysis, without much statistical rigor.

Generally speaking, there is not very much power in any branch-site type method, even if the 'foreground' branch is specified a priori (as shown by poor power in simulation studies by Yang et al in their 2005 MBE paper). Also, there is a problem of model mis-specification (i.e. postulating which branches are under selection).

Cheers,
Sergei