[Biojava-l] Subtle bug in SimpleDistribution

[Schreiber, Mark]

Actually, after looking with a debugger I found that a programming error
on my part was causing the addition of negative counts to the
distribution. Perhaps either SimpleDistributionTrainerContext or
SimpleDistribution.Trainer could be made to throw an exception in such a
case so as to make it more idiot proof

Mark


Mark Schreiber
Bioinformatics
AgResearch Invermay
PO Box 50034
Mosgiel
New Zealand

PH: +64 3 489 9175

 

> -----Original Message-----
> From: Matthew Pocock [mailto:matthew_pocock@yahoo.co.uk]
> Sent: Friday, January 18, 2002 11:29 AM
> To: Schreiber, Mark
> Cc: biojava-l (E-mail)
> Subject: Re: [Biojava-l] Subtle bug in SimpleDistribution
> 
> 
> Hi Mark,
> 
> What are the symptoms of your bug? The handling of ambiguous counts 
> should be implemented by:
> 
> DistributionTrainerContext.addCount(
>    Distribution dist,
>    Symbol sym,
>    double times)
> 
> This passes the count on to:
> 
> DistributionTrainer.addCount(
>    AtomicSymbol aSym,
>    double times)
> 
> Is this chain of events not getting fired off for you?
> 
> There's a larger question over how to treat ambiguities 
> during training. 
> I have come to the opinion that a sequence with an ambiguity in it is 
> actualy a set of un-ambiguous sequences that match the 
> ambiguous symbols 
> in all possible ways. This makes the maths work out better 
> than saying 
> that it is partly one sequence and partly another. If you use 
> the odds 
> measurements during DP then this all divides out to give the expected 
> likelihoods for alignments. However, it makes P(seq | model) equal to 
> sum_i(seq_i | model) if there are i unambiguous sequences that could 
> match your sequence by chosing matches for all combinations of all 
> ambiguous symbols. Be aware. An obvious result of this is 
> that a string 
> of N's has the maximal probability of all sequences that length being 
> aligned to a model, where as the odds of a string of N's 
> being aligned 
> will be 0 as there is no information relative to the null 
> model to consider.
> 
> Feel free to tell me this is all pants and come up with a 
> more sensible 
> scheim for all of this. Anyone out there know some probability theory?
> 
> Matthew
> 
> Schreiber, Mark wrote:
> 
> > Well maybe not a bug but a potential danger.
> > 
> > SimpleDistribution.Trainer will accept counts from 
> ambiguity symbols (N)
> > and the Gap symbol however when it comes to train it uses the
> > AlphabetIndexer for DNA which does not include indices for 
> these symbols
> > and this leads to some very odd results.
> > 
> > A number of solutuions might exist:
> > 
> > 1) prevent the addition of ambiguos symbols to
> > SimpleDistribution.Trainer. Safe, but an unexpected N in 
> your sequence
> > could cause an unexpected exception so not very user freindly.
> > 
> > 2) refactor SimpleDistribution.Trainer to add equal numbers 
> of counts to
> > ambiguity subsymbols. ie if N is added then add 1 count to each of
> > a,c,g,t. However this will not work for gap symbols.
> > 
> > 3) extend the dna AlphabetIndex to include IUPAC ambiguities
> > (m,r,w,s,y,k,v,h,d,b,n) and the gap symbol. Solves the gap 
> problem but
> > maybe N should be added as one count to each of its subsymbols.
> > 
> > Not sure I like any of these, any other suggestions??
> > 
> > 
> > Mark Schreiber
> > Bioinformatics
> > AgResearch Invermay
> > PO Box 50034
> > Mosgiel
> > New Zealand
> > 
> > PH: +64 3 489 9175
> > 
> >  
> > 
> > 
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> 
> 
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