Hi Eleni,
Although progressiveMauve's algorithm is deterministic for a fixed
input, the algorithm itself contains some stochastic elements,
especially when aligning regions between the initial set of unique
alignment anchors. Therefore, changes to the input such as order of
genomes, or possibly ordering of contigs within genomes, can change the
resulting alignment.
It sounds like your one of your genomes contains a potential
rearrangement, possibly related to repeat elements, that has a score
very close to the default LCB score thresholds being used by
progressiveMauve. Although the default parameters were tuned to produce
good results on a wide range of datasets there is nothing sacred about
them, they can be changed to produce better results if necessary. I do
wonder if a positional homology alignment might miss part of the
picture on your data though, it may be worthwhile to check for repeat
structure across your genomes using another method.
Best,
-Aaron
On Wed, 2017-03-01 at 12:09 -0600, Eleni Mijalis wrote:
> Images didn't come through, sorry. Please see attached.
>
> On Wed, Mar 1, 2017 at 12:01 PM, Eleni Mijalis <elenimija...@tamu.edu
> > wrote:
> > Hey there,
> >
> > I am having issues with getting different alignment results based
> > on the ordering of input files.
> >
> > I am aligning 7 genomes, and this is these are two examples of
> > alignments differing based on order:
> >
> >
> >
> >
> > As you can see, the first example gives 1 LCB spanning the entirety
> > of all the genomes, and the second example (same genomes, different
> > order) has more LCBs spanning different areas of each genome. These
> > two are just samples of what output I get based on input
> > permutation.
> >
> > I am using default parameters, so should I adjust parameters to get
> > more consistent results? Why would ordering matter when determining
> > regions of similarity? Thanks for your help.
> >
> > Eleni
> >
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--
Aaron E. Darling, Ph.D.
Associate Professor, ithree institute
University of Technology Sydney
Australia
http://darlinglab.org
twitter: @koadman
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