Bio::Align::DNAStatistics - Calculate some statistics for a DNA alignment
use Bio::AlignIO;
use Bio::Align::DNAStatistics;
my $stats = Bio::Align::DNAStatistics->new();
my $alignin = Bio::AlignIO->new(-format => 'emboss',
-file => 't/data/insulin.water');
my $aln = $alignin->next_aln;
my $jcmatrix = $stats->distance(-align => $aln,
-method => 'Jukes-Cantor');
print $jcmatrix->print_matrix;
## and for measurements of synonymous /nonsynonymous substitutions ##
my $in = Bio::AlignIO->new(-format => 'fasta',
-file => 't/data/nei_gojobori_test.aln');
my $alnobj = $in->next_aln;
my ($seq1id,$seq2id) = map { $_->display_id } $alnobj->each_seq;
my $results = $stats->calc_KaKs_pair($alnobj, $seq1id, $seq2id);
print "comparing ".$results->[0]{'Seq1'}." and ".$results->[0]{'Seq2'}."\n";
for (sort keys %{$results->[0]} ){
next if /Seq/;
printf("%-9s %.4f \n",$_ , $results->[0]{$_});
}
my $results2 = $stats->calc_all_KaKs_pairs($alnobj);
for my $an (@$results2){
print "comparing ". $an->{'Seq1'}." and ". $an->{'Seq2'}. " \n";
for (sort keys %$an ){
next if /Seq/;
printf("%-9s %.4f \n",$_ , $an->{$_});
}
print "\n\n";
}
my $result3 = $stats->calc_average_KaKs($alnobj, 1000);
for (sort keys %$result3 ){
next if /Seq/;
printf("%-9s %.4f \n",$_ , $result3->{$_});
}
This object contains routines for calculating various statistics and distances
for DNA alignments. The routines are not well tested and do contain errors at
this point. Work is underway to correct them, but do not expect this code to
give you the right answer currently! Use dnadist/distmat in the PHLYIP or
EMBOSS packages to calculate the distances.
Several different distance method calculations are supported. Listed in brackets
are the pattern which will match
- •
- JukesCantor [jc|jukes|jukescantor|jukes-cantor]
- •
- Uncorrected [jcuncor|uncorrected]
- •
- F81 [f81|felsenstein]
- •
- Kimura [k2|k2p|k80|kimura]
- •
- Tamura [t92|tamura|tamura92]
- •
- F84 [f84|felsenstein84]
- •
- TajimaNei [tajimanei|tajima\-nei]
- •
- JinNei [jinnei|jin\-nei] (not implemented)
There are also three methods to calculate the ratio of synonymous to
non-synonymous mutations. All are implementations of the Nei-Gojobori
evolutionary pathway method and use the Jukes-Cantor method of nucleotide
substitution. This method works well so long as the nucleotide frequencies are
roughly equal and there is no significant transition/transversion bias. In
order to use these methods there are several pre-requisites for the alignment.
- 1.
- DNA alignment must be based on protein alignment. Use the
subroutine "aa_to_dna_aln" in Bio::Align::Utilities to achieve
this.
- 2.
- Therefore alignment gaps must be in multiples of 3
(representing an aa deletion/insertion) and at present must be indicated
by a '-' symbol.
- 3.
- Alignment must be solely of coding region and be in reading
frame 0 to achieve meaningful results
- 4.
- Alignment must therefore be a multiple of 3 nucleotides
long.
- 5.
- All sequences must be the same length (including gaps).
This should be the case anyway if the sequences have been automatically
aligned using a program like Clustal.
- 6.
- Only the standard codon alphabet is supported at
present.
calc_KaKs_pair() calculates a number of statistics for a named pair of
sequences in the alignment.
calc_all_KaKs_pairs() calculates these statistics for all pairwise
comparisons in an MSA. The statistics returned are:
- •
- S_d - Number of synonymous mutations between the 2
sequences.
- •
- N_d - Number of non-synonymous mutations between the 2
sequences.
- •
- S - Mean number of synonymous sites in both sequences.
- •
- N - mean number of synonymous sites in both sequences.
- •
- P_s - proportion of synonymous differences in both
sequences given by P_s = S_d/S.
- •
- P_n - proportion of non-synonymous differences in both
sequences given by P_n = S_n/S.
- •
- D_s - estimation of synonymous mutations per synonymous
site (by Jukes-Cantor).
- •
- D_n - estimation of non-synonymous mutations per
non-synonymous site (by Jukes-Cantor).
- •
- D_n_var - estimation of variance of D_n .
- •
- D_s_var - estimation of variance of S_n.
- •
- z_value - calculation of z value.Positive value indicates
D_n > D_s, negative value indicates D_s > D_n.
The statistics returned by calc_average_KaKs are:
- •
- D_s - Average number of synonymous mutations/synonymous
site.
- •
- D_n - Average number of non-synonymous
mutations/non-synonymous site.
- •
- D_s_var - Estimated variance of Ds from bootstrapped
alignments.
- •
- D_n_var - Estimated variance of Dn from bootstrapped
alignments.
- •
- z_score - calculation of z value. Positive value indicates
D_n >D_s, negative values vice versa.
The design of the code is based around the explanation of the Nei-Gojobori
algorithm in the excellent book "Molecular Evolution and
Phylogenetics" by Nei and Kumar, published by Oxford University Press.
The methods have been tested using the worked example 4.1 in the book, and
reproduce those results. If people like having this sort of analysis in
BioPerl other methods for estimating Ds and Dn can be provided later.
Much of the DNA distance code is based on implementations in EMBOSS (Rice et al,
www.emboss.org) [distmat.c] and PHYLIP (J. Felsenstein et al) [dnadist.c].
Insight also gained from Eddy, Durbin, Krogh, & Mitchison.
- •
- D_JukesCantor
"Phylogenetic Inference", Swoffrod, Olsen, Waddell and Hillis, in
Mol. Systematics, 2nd ed, 1996, Ch 11. Derived from "Evolution of
Protein Molecules", Jukes & Cantor, in Mammalian Prot. Metab.,
III, 1969, pp. 21-132.
- •
- D_Tamura
K Tamura, Mol. Biol. Evol. 1992, 9, 678.
- •
- D_Kimura
M Kimura, J. Mol. Evol., 1980, 16, 111.
- •
- JinNei
Jin and Nei, Mol. Biol. Evol. 82, 7, 1990.
- •
- D_TajimaNei
Tajima and Nei, Mol. Biol. Evol. 1984, 1, 269.
User feedback is an integral part of the evolution of this and other Bioperl
modules. Send your comments and suggestions preferably to the Bioperl mailing
list. Your participation is much appreciated.
[email protected] - General discussion
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Please direct usage questions or support issues to the mailing list:
[email protected]
rather than to the module maintainer directly. Many experienced and reponsive
experts will be able look at the problem and quickly address it. Please
include a thorough description of the problem with code and data examples if
at all possible.
Report bugs to the Bioperl bug tracking system to help us keep track of the bugs
and their resolution. Bug reports can be submitted via the web:
https://github.com/bioperl/bioperl-live/issues
Email jason-AT-bioperl.org
Richard Adams,
[email protected]
The rest of the documentation details each of the object methods. Internal
methods are usually preceded with a _
Title : new
Usage : my $obj = Bio::Align::DNAStatistics->new();
Function: Builds a new Bio::Align::DNAStatistics object
Returns : Bio::Align::DNAStatistics
Args : none
Title : distance
Usage : my $distance_mat = $stats->distance(-align => $aln,
-method => $method);
Function: Calculates a distance matrix for all pairwise distances of
sequences in an alignment.
Returns : L<Bio::Matrix::PhylipDist> object
Args : -align => Bio::Align::AlignI object
-method => String specifying specific distance method
(implementing class may assume a default)
See also: L<Bio::Matrix::PhylipDist>
Title : available_distance_methods
Usage : my @methods = $stats->available_distance_methods();
Function: Enumerates the possible distance methods
Returns : Array of strings
Args : none
Title : D_JukesCantor
Usage : my $d = $stat->D_JukesCantor($aln)
Function: Calculates D (pairwise distance) between 2 sequences in an
alignment using the Jukes-Cantor 1 parameter model.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> of DNA sequences
double - gap penalty
Title : D_F81
Usage : my $d = $stat->D_F81($aln)
Function: Calculates D (pairwise distance) between 2 sequences in an
alignment using the Felsenstein 1981 distance model.
Relaxes the assumption of equal base frequencies that is
in JC.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> of DNA sequences
Title : D_Uncorrected
Usage : my $d = $stats->D_Uncorrected($aln)
Function: Calculate a distance D, no correction for multiple substitutions
is used. In rare cases where sequences may not overlap, 'NA' is
substituted for the distance.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> (DNA Alignment)
[optional] gap penalty
Title : D_Kimura
Usage : my $d = $stat->D_Kimura($aln)
Function: Calculates D (pairwise distance) between all pairs of sequences
in an alignment using the Kimura 2 parameter model.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> of DNA sequences
Title : D_Kimura
Usage : my $d = $stat->D_Kimura_variance($aln)
Function: Calculates D (pairwise distance) between all pairs of sequences
in an alignment using the Kimura 2 parameter model.
Returns : array of 2 L<Bio::Matrix::PhylipDist>,
the first is the Kimura distance and the second is
a matrix of variance V(K)
Args : L<Bio::Align::AlignI> of DNA sequences
Title : D_Tamura
Usage : Calculates D (pairwise distance) between 2 sequences in an
alignment using Tamura 1992 distance model.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> of DNA sequences
Title : D_F84
Usage : my $d = $stat->D_F84($aln)
Function: Calculates D (pairwise distance) between 2 sequences in an
alignment using the Felsenstein 1984 distance model.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> of DNA sequences
[optional] double - gap penalty
Title : D_TajimaNei
Usage : my $d = $stat->D_TajimaNei($aln)
Function: Calculates D (pairwise distance) between 2 sequences in an
alignment using the TajimaNei 1984 distance model.
Returns : L<Bio::Matrix::PhylipDist>
Args : Bio::Align::AlignI of DNA sequences
Title : D_JinNei
Usage : my $d = $stat->D_JinNei($aln)
Function: Calculates D (pairwise distance) between 2 sequences in an
alignment using the Jin-Nei 1990 distance model.
Returns : L<Bio::Matrix::PhylipDist>
Args : L<Bio::Align::AlignI> of DNA sequences
Title : transversions
Usage : my $transversions = $stats->transversion($aln);
Function: Calculates the number of transversions between two sequences in
an alignment
Returns : integer
Args : Bio::Align::AlignI
Title : transitions
Usage : my $transitions = Bio::Align::DNAStatistics->transitions($aln);
Function: Calculates the number of transitions in a given DNA alignment
Returns : integer representing the number of transitions
Args : Bio::Align::AlignI object
Title : pairwise_stats
Usage : $obj->pairwise_stats($newval)
Function:
Returns : value of pairwise_stats
Args : newvalue (optional)
Title : calc_KaKs_pair
Useage : my $results = $stats->calc_KaKs_pair($alnobj,
$name1, $name2).
Function : calculates Nei-Gojobori statistics for pairwise
comparison.
Args : A Bio::Align::AlignI compliant object such as a
Bio::SimpleAlign object, and 2 sequence name strings.
Returns : a reference to a hash of statistics with keys as
listed in Description.
Title : calc_all_KaKs_pairs
Useage : my $results2 = $stats->calc_KaKs_pair($alnobj).
Function : Calculates Nei_gojobori statistics for all pairwise
combinations in sequence.
Arguments: A Bio::Align::ALignI compliant object such as
a Bio::SimpleAlign object.
Returns : A reference to an array of hashes of statistics of
all pairwise comparisons in the alignment.
Title : calc_average_KaKs.
Useage : my $res= $stats->calc_average_KaKs($alnobj, 1000).
Function : calculates Nei_Gojobori stats for average of all
sequences in the alignment.
Args : A Bio::Align::AlignI compliant object such as a
Bio::SimpleAlign object, number of bootstrap iterations
(default 1000).
Returns : A reference to a hash of statistics as listed in Description.
Title : get_syn_changes
Usage : Bio::Align::DNAStatitics->get_syn_changes
Function: Generate a hashref of all pairwise combinations of codns
differing by 1
Returns : Symetic matrix using hashes
First key is codon
and each codon points to a hashref of codons
the values of which describe type of change.
my $type = $hash{$codon1}->{$codon2};
values are :
1 synonymous
0 non-syn
-1 either codon is a stop codon
Args : none
Title : dnds_pattern_number
Usage : my $patterns = $stats->dnds_pattern_number($alnobj);
Function: Counts the number of codons with no gaps in the MSA
Returns : Number of codons with no gaps ('patterns' in PAML notation)
Args : A Bio::Align::AlignI compliant object such as a
Bio::SimpleAlign object.