Bio::Align::DNAStatistics - Calculate some statistics for a DNA alignment use Bio::AlignIO; use Bio::Align::DNAStatistics; my $stats = new Bio::Align::DNAStatistics; my $alignin = new Bio::AlignIO(-format => 'emboss', -file => 't/data/insulin.water'); my $aln = $alignin->next_aln; my $jc = $stats->distance(-align => $aln, -method => 'Jukes-Cantor'); foreach my $d ( @$jc ) { print "\t"; foreach my $r ( @$d ) { print "$r\t"; } print "\n"; } ## and for measurements of synonymous /nonsynonymous substitutions ## my $in = new Bio::AlignIO(-format => 'fasta', -file => 't/data/nei_gojobori_test.aln'); my $alnobj = $in->next_aln; my ($seqid,$seq2id) = map { $_->display_id } $alnobj->each_seq; my $results = $stats->calc_KaKs_pair($alnobj, $seqid, $seq2id); print "comparing ".$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. 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. DNA alignment must be based on protein alignment. Use the subroutine aa_to_dna_aln in Bio::Align::Utilities to achieve this. Therefore alignment gaps must be in multiples of 3 (representing an aa deletion/insertion) and at present must be indicated by a '-' symbol. Alignment must be solely of coding region and be in reading frame 0 to achieve meaningful results ALignment must therefore be a multiple of 3 nucleotides long. 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. 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: Number of synonymous mutations between the 2 sequences. Number of non-synonymous mutations between the 2 sequences. Mean number of synonymous sites in both sequences. mean number of synonymous sites in both sequences. proportion of synonymous differences in both sequences given by P_s = S_d/S. proportion of non-synonymous differences in both sequences given by P_n = S_n/S. estimation of synonymous mutations per synonymous site (by Jukes-CAntor). estimation of non-synonymous mutations per non-synonymous site (by Jukes-CAntor). estimation of variance of D_n . estimation of variance of S_n. 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: Average number of synonymous mutations/synonymous site. Average number of non-synonymous mutations/non-synonymous site. Estimated variance of Ds from bootstrapped alignments. Estimated variance of Dn from bootstrapped alignments. 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.

Mailing Lists
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. bioperl-l@bioperl.org - General discussion http://bioperl.org/MailList.shtml - About the mailing lists

Reporting Bugs
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 email or the web: bioperl-bugs@bioperl.org http://bugzilla.bioperl.org/ Email jason@bioperl.org Describe contact details here Additional contributors names and emails here Richard Adams, richard.adams@ed.ac.uk The rest of the documentation details each of the object methods. Internal methods are usually preceded with a _

new
Title : new Usage : my $obj = new Bio::Align::DNAStatistics(); Function: Builds a new Bio::Align::DNAStatistics object Returns : Bio::Align::DNAStatistics Args : none

distance
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 : Array ref Args : -align => Bio::Align::AlignI object -method => String specifying specific distance method (implementing class may assume a default)

available_distance_methods
Title : available_distance_methods Usage : my @methods = $stats->available_distance_methods(); Function: Enumerates the possible distance methods Returns : Array of strings Args : none

D - distance methods

D_JukesCantor
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 : ArrayRef of all pairwise distances of all sequence pairs in the alignment Args : Bio::Align::AlignI of DNA sequences double - gap penalty

D_F81
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. Returns : ArrayRef of a 2d array of all pairwise distances in the alignment Args : Bio::Align::AlignI of DNA sequences

D_Kimura
Title : D_Kimura Usage : my $d = $stat->D_Kimura($aln) Function: Calculates D (pairwise distance) between 2 sequences in an alignment using the Kimura 2 parameter model. Returns : ArrayRef of pairwise distances between all sequences in alignment Args : Bio::Align::AlignI of DNA sequences

D_Tamura
Title : D_Tamura Usage : Function: Returns : Args :

D_F84
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 : Distance value Args : Bio::Align::AlignI of DNA sequences double - gap penalty

D_TajimaNei
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 : Distance value Args : Bio::Align::AlignI of DNA sequences

K - sequence substitution methods

K_JukesCantor
Title : K_JukesCantor Usage : my $k = $stats->K_JukesCantor($aln) Function: Calculates K - the number of nucleotide substitutions between 2 seqs - according to the Jukes-Cantor 1 parameter model This only involves the number of changes between two sequences. Returns : double Args : Bio::Align::AlignI

K_TajimaNei
Title : K_TajimaNei Usage : my $k = $stats->K_TajimaNei($aln) Function: Calculates K - the number of nucleotide substitutions between 2 seqs - according to the Kimura 2 parameter model. This does not assume equal frequencies among all the nucleotides. Returns : ArrayRef of 2d matrix which contains pairwise K values for all sequences in the alignment Args : Bio::Align::AlignI

transversions
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

transitions
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

Data Methods

pairwise_stats
Title : pairwise_stats Usage : $obj->pairwise_stats($newval) Function: Returns : value of pairwise_stats Args : newvalue (optional)

calc_KaKs_pair
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.

calc_all_KaKs_pairs
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.

calc_average_KaKs
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.

get_syn_changes
Title : get_syn_changes Usage : Bio::Align::DNAStatitics->get_syn_chnages 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 synonomous 0 non-syn -1 either codon is a stop codon Args : none