| Calling Sequence
| PSDynProg(ps1,ps2,dist,meth)
PSDynProg(ps1,ps2,dist,lnM,freq,gapcosts,meth)
|
| Parameters
| | Name | Type | Description |
|
| ps1, ps2
| ProbSeq | Probabilistic sequences |
| dist
| numeric | Distance between the two sequences |
| lnM
| matrix(numeric) | (optional) log. of a 1-PAM matrix |
| freq
| array(numeric) | (optional) Natural frequencies of the characters |
| gapcosts
| procedure | (optional) Gapcosts as a function of gap length |
| meth
| {Global,Local} | (optional) alignment method |
|
| Return Type
| [numeric, ProbSeq, ProbSeq] |
| Globals
| DBGTMP, |
| Synopsis
| Dynamic programming over two probabilistic sequences. In the standard case
of proteins, the global varibles NewLogPAM1, AF and gap costs according to the Dayhoff
matrices are used. For other types of sequences (e.g. DNA or codons),
the logarithm of a mutation matrix (e.g. CodonLogPAM1) and the natural
frequencies of the characters (e.g. CF) are required. Also, a gap cost function is needed that returns
the costs for a gap of a given size. This is usually k->FixedDel+(k-1)*IncDel with the coefficients
taken from the CMS matrix for the given distance.
The default alignment method is 'Local'. |
| References
| GM Cannarozzi, A Schneider and GH Gonnet (2007): Probabilistic Ancestral Sequences Based on the Markovian Model of Evolution - Algorithms and Applications, in: D Liberless (editor): Ancestral Sequence Reconstruction, Oxford University Press. |
| Examples
| > ps1 := ProbSeq('RAAVTGAAAQQQFT',IntToA):
> ps2 := ProbSeq('VTGQQQ',IntToA):
> dist := 10:
> aps := PSDynProg(ps1,ps2,dist):
> print(aps);;
41.6760
pos Most probable chars
1 V 1.00
2 T 1.00
3 G 1.00
4 A 1.00
5 A 1.00
6 A 1.00
7 Q 1.00
8 Q 1.00
9 Q 1.00
pos Most probable chars
1 V 1.00
2 T 1.00
3 G 1.00
4 <gap>
5 <gap>
6 <gap>
7 Q 1.00
8 Q 1.00
9 Q 1.00
|
| See also
| CreateCodonMatrices, CreateDayMatrices, PASfromMSA, PASfromTree, ProbAncestor, ProbSeq |