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BioPerl-1.7.7
River stage two • 60 direct dependents • 65 total dependents
/ Bio::Align::DNAStatistics

NAME

Bio::Align::DNAStatistics - Calculate some statistics for a DNA alignment

SYNOPSIS

  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 %$result3 ){
      next if /Seq/;
      printf("%-9s %.4f \n",$_ , $result3->{$_});
  }

DESCRIPTION

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.

REFERENCES

  • 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.

FEEDBACK

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/wiki/Mailing_lists  - About the mailing lists

Support

Please direct usage questions or support issues to the mailing list:

bioperl-l@bioperl.org

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.

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 the web:

https://github.com/bioperl/bioperl-live/issues

AUTHOR - Jason Stajich

Email jason-AT-bioperl.org

CONTRIBUTORS

Richard Adams, richard.adams@ed.ac.uk

APPENDIX

The rest of the documentation details each of the object methods. Internal methods are usually preceded with a _

new

Title   : new
Usage   : my $obj = Bio::Align::DNAStatistics->new();
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 : 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>

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 : L<Bio::Matrix::PhylipDist>
Args    : L<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. 
          Relaxes the assumption of equal base frequencies that is
          in JC.
Returns : L<Bio::Matrix::PhylipDist>
Args    : L<Bio::Align::AlignI> of DNA sequences

D_Uncorrected

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

D_Kimura

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

D_Kimura_variance

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

D_Tamura

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

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 : L<Bio::Matrix::PhylipDist>
Args    : L<Bio::Align::AlignI> of DNA sequences
          [optional] 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 : L<Bio::Matrix::PhylipDist>
Args    : Bio::Align::AlignI of DNA sequences

D_JinNei

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

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_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

dnds_pattern_number

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.