G::Seq GCskew
SummaryIncluded librariesPackage variablesDescriptionGeneral documentationMethods
Summary
    G::Seq::GCskew - Analysis methods related to GC skew and genomic strand bias
Package variables
No package variables defined.
Included modules
G::Messenger
G::Seq::Primitive
G::Tools::Graph
G::Tools::Statistics
SelfLoader
SubOpt
autouse ' Algorithm::Numerical::Shuffle ' => qw ( shuffle )
Inherit
Exporter
Synopsis
No synopsis!
Description
    This class is a part of G-language Genome Analysis Environment, 
    collecting sequence analysis methods related to GC skew.
Methods
cum_gcskew
No description
Code
dist_in_ccDescriptionCode
find_ori_terDescriptionCode
gcsiDescriptionCode
gcskewDescriptionCode
gcwinDescriptionCode
genes_from_oriDescriptionCode
genomicskewDescriptionCode
leading_strandDescriptionCode
query_armDescriptionCode
query_strandDescriptionCode
rep_ori_terDescriptionCode
set_gc3DescriptionCode
set_strandDescriptionCode
Methods description
dist_in_cccode    nextTop
 Name: dist_in_cc   -   calculates the distance between two loci in circular chromosomes

 Description:
   This program calculates the distance between two loci in 
   circular chromosomes, mostly useful to calculate the
   distance from the replication origin.

  Usage: int distance = dist_in_cc(G instance, int position1, int position2);

 Options:
   If the second position is not given, position of replication origin is used.

 Note:
   Origin and terminus of replication is obtained from rep_ori_ter()

 Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20070112-01 initial posting
find_ori_tercodeprevnextTop
 Name: find_ori_ter   -   predict the replication origin and terminus in bacterial genomes

 Description:
    Predicts the replicational origin and terminus in circular bacterial genomes,
    by taking the vertices of cumulative skew graphs (GC, keto, or purine). See
    Reference 1 for the basic idea behind thid algorithm (but also note that this
    algorithm is different from that of Oriloc, which uses GC3 of genes). 

    Terminus of replication can be more accurate by using noise-reduction 
    filtering using Fourier spectrum of the GC skew. This low-pass filtering
    can be applied using -filter option. See Reference 2 for details.

 Usage:
    ($origin, $terminus) = find_ori_ter($genome);

 Options:
   -output    output toggle option (default: stdout)
   -purine    use purine skew for calculation (default: 0)
   -keto      use keto skew for calculation (default: 0)
   -filter    lowpass filter strength in percent. typically 95 or 99 works best. (default: NULL)
   -window    number of windows to use for Fast Fourier Transform. only active 
              when -filter option is specified. value must be the power of two. (default: 4096)

 References:
   1. Frank AC, Lobry JR (2000) "Oriloc: prediction of replication boundaries in unannotated 
      bacterial chromosomes", Bioinformatics, 16:566-567.
   2. Arakawa K, Saito R, Tomita M (2007) "Noise-reduction filtering for accurate detection 
      of replication termini in bacterial genomes", FEBS Letters, 581(2):253-258.

 Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20071023-01 speed up by combining rough/detailed searches 20070707-01 added -filter option 20060711-01 added purine and keto options 20060707-01 calculation is now based on single bp resolution rather than with windows but now it is a lot more slower... 20060221-01 speed up using Statistics::Descriptive 20010905-01 options update 20010326-01 initial posting
gcsicodeprevnextTop
  Name: gcsi   -   GC Skew Index: an index for strand-specific mutational bias

  Description:
    This program calculates the GC Skew Index (GCSI) of the given circular
    bacterial genome. GCSI quantifies the degree of GC Skew. In other words,
    this index represents the degree of strand-specific mutational bias in 
    bacterial genomes, caused by replicational selection. 

    GCSI is calculated by the following formula:
        GCSI = sqrt((SA/6000) * (dist/600))
    where SA is the spectral amplitude of Fourier power spectrum at 1Hz,
    and dist is the normalized Euclidean distance between the vertices of 
    cumulative GC skew.

    GCSI ranges from 0 (no observable skew) to 1 (strong skew), and Archaeal genomes
    that have multiple replication origins and therefore have no observable skew
    mostly have GCSI below 0.05. Escherichia coli genome has values around 0.10.

    Version 1 of GCSI required fixed number of windows (4096), but the new GCSI
    version 2 (also known as generalized GCSI: gGCSI) is invariant of the number
    of windows. GCSI version 1 is calculated as an arithmetic mean (as opposed to 
    the geometric mean of gGCSI) of SR (spectral ratio, the signal-to-noise ratio
    of 1Hz power spectrum) and dist. 

  Usage: 
    $gcsi = gcsi($genome);               # scalar context
       or
    ($gcsi, $sa, $dist) = gcsi($genome); # array context

  Options:
   -version     version of GCSI. generalized GCSI is selected by default. (default: 2)
   -window      number of windows. must be a power of 2. (default: 4096)
   -purine      use purine skew for calculation (default: 0)
   -keto        use keto skew for calculation (default: 0)
   -at          use AT skew for calculation (default: 0)
   -p           calculate p-value when GCSI version 2 is selected (default: 0)
                returned values are ($gcsi, $sa, $dist, $z, $p)

  References:
    1. Arakawa K, Tomita M (2007) "The GC skew index: a measure of genomic compositional 
       asymmetry and the degree of replicational selection", Evolutionary Bioinformatics, 3:145-154.

  Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20090311-01 updated to version 2, with -p and -version options 20080421-01 added -at, -purine and -keto options 20070313-01 added error message for when genome size is too small 20070707-01 initial posting
gcskewcodeprevnextTop
 Name: gcskew   -   calculate the GC skew of the given genome

 Description:
   This program calculates and graphs the GC skew. 

 Usage: 
    array @gcskew = gcskew(G instance);

 Options:
   -window      window size to observe (default: 10000)
   -slide       window slide size (default: same as window size)
   -cumulative  1 to calculate cumulative skew (default: 0)
   -at          1 when observing AT skew instead of GC skew (default: 0)
   -purine      1 when observing purine (AG/TC) skew (default: 0)
   -keto        1 when observing keto (TG/AC) skew (default: 0)
   -output      f for file output in directory "data", 
                g for graph output in directory "graph",
                show for graph output and display (default: "show")
   -filename    output filename (default: "gcskew.png" for -output=>"g",
                                          "gcskew.csv" for -output=>"f")

 Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20090601-01 added -slide option 20070707-01 added -cumulative option 20060711-01 added purine and keto skew 20010905-01 update with options 20010727-01 initial posting
gcwincodeprevnextTop
 Name: gcwin   -   calculate the GC content along the given genome

 Description:
   This program calculates and graphs the GC content.

 Usage: 
    array @gcwin = gcwin(G instance);

 Options:
   -window      window size to observe (default: 10000)
   -at          1 when observing AT content instead of GC content (default: 0)
   -purine      1 when observing purines (AG) skew (default: 0)
   -keto        1 when observing ketos (TG) skew (default: 0)
   -output      f for file output in directory "data", 
                g for graph output in directory "graph",
                show for graph output and display (default: "show")
   -filename    output filename (default: "gcwin.png" for -output=>"g",
                                          "gcwin.csv" for -output=>"f")

 Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20091007-01 changed to disregard N or X bases 20070429-01 minor bug fix related to output=>"f" option 20060711-01 added purine and keto options 20010905-01 updated options 20010729-01 initial posting
genes_from_oricodeprevnextTop
 Name: genes_from_ori   -   get a list of CDS IDs ordered in the distance from origin of replication

 Description:
   This program lists genes in order relative to the position of 
   replication origin in either right or left half of the bacterial
   chromosomes.

  Usage: array @genes = genes_from_ori(G instance, "right");

 Options:
   Second argument should be eighter "right" or "left" to indicate
   the interested half of the bacterial chromosome. If omitted, 
   returns list of genes on both arms in the order of distance
   from replication origin.

 Note:
   Origin and terminus of replication is obtained from rep_ori_ter()

 Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20070106-01 initial posting 20070112-01 modified the handling of second argument
genomicskewcodeprevnextTop
 Name: genomicskew   -   calculate the GC skew in different  regions of the given genome

 Description:
   This program graphs the GC skew for the whole genome, coding regions,
   intergenic regions, and the third codon.

 Usage: 
   (\@gcskew, \@geneskew, \@betskew, \@thirdskew) = genomicskew($genome);

 Options:
   -divide      window number to divide into (default: 250)
   -at          1 when observing AT skew instead of GC skew (default: 0)
   -output      f for file output in directory "data", 
                g for graph output in directory "graph",
                show for graph output and display (default: "show")
   -filename    output filename (default: "genomicskew.png" for -output=>"g",
                                          "genomicskew.csv" for -output=>"f")
   -application application to open png image (default: "gimv")

 Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20090313-01 updated according to the update of $gb->intergenic() to include stable RNA genes as genetic elements 20080421-01 now returns references of result arrays 20040610-01 updated to handle introns and exons 20040601-01 bug fix for output=>"f" option 20010905-01 updated options 20010727-01 initial posting
leading_strandcodeprevnextTop
 Name: leading_strand   -   get the sequences of leading strands

 Description:
   This method returns the leading strands from origin and terminus 
   of replication calculated with rep_ori_ter().

   When called in array context, this method returns the sequences
   of the two replication arms. In scalar context, the sequences of
   the two arms are concatenated and returned as one sequence.

 Usage: 
    #in array context
    ($arm1, $arm2) = leading_strand($genome);

    #in scalar context
    string $leadingStrand = leading_strand($genome);

 Options:
    none

  Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20071022-01 added array/scalar contexts 20011030-01 initial posting
query_armcodeprevnextTop
  Name: query_arm   -   get the replication arm name (left or right) from the given position

  Description:
    Given a position, returns whether the specified position is in the 
    left or right arm of the circular chromosome.

  Usage: 
    string arm = query_arm(G instance, int position);

  Options: 
    None.

  Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20070112-01 initial posting
query_strandcodeprevnextTop
  Name: query_strand   -   get the strand name (leading or lagging) from the given position

  Description:
    Given a position and strand information (direct or complement), 
    returns whether the specified position is in the leading or lagging strand.

  Usage: 
    string strand = query_strand(G instance, int position);

    or

    string strand = query_strand(G instance, CDS/FEATURE id);

 Options: 
    -direction    strand of the querying position, either 'direct' or 'complement'
                  (default: direct)

  Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20070106-01 added CDS option 20020218-01 initial posting
rep_ori_tercodeprevnextTop
 Name: rep_ori_ter   -   get the positions of replication origin and terminus

 Description:
    This method returns the documented replicational origin and terminus.
    Currently positions are available in the following genomes:
     [1] Escherichia coli K12, Bacillus subtilis, Haemophilus influenzae
     [2] Salmonella typhi

    If "rep_origin" feature is available, center position within this feature
    is used for origin. 

    If no documentation is available, the origin and terminus is predicted using
    find_ori_ter().

    After calling this function, positions of origin and terminus are stored 
    as follows:
      $genome->{FEATURE0}->{origin}
      $genome->{FEATURE0}->{terminus}

 Usage: 
    ($ori, $ter) = rep_ori_ter($genome);

 References:
   1. Freeman JM et al. (1998) "Patterns of Genome Organization in Bacteria", 
      Science, 279(5358):1827a
   2. Parkhill J et al. (2001) "Complete genome sequence of a multiple drug 
      resistant Salmonella enterica serovar Typhi CT18", Nature, 413(6858):848-852 

 Options:
   none

 Author: Kazuharu Arakawa

 History:
    20080428-01 added support for "rep_origin" feature
    20011030-01 initial posting
set_gc3codeprevnextTop
  Name: set_gc3   -   set GC content in 3rd codon position of all genes

  Description:
    Sets $gb->{$cds}->{gc3}, GC content in 3rd codon position.
    Value is in decimal (eg. 0.56345).

  Usage: 
    1 = set_gc3($gb)

 Options: 
    None.

  Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20070116-01 initial posting
set_strand codeprevnextTop
  Name: set_strand   -   set replication strand and arm information to given G instance

  Description:
    Sets $gb->{$cds}->{strand} and $gb->{$cds}->{arm} using
    query_strand() and query_arm(), indicating in which strand
    or replication arm the gene resides.

  Usage: 
    1 = set_strand($gb)

 Options: 
    None.

  Author: 
    Kazuharu Arakawa (gaou@sfc.keio.ac.jp)
History: 20070112-01 initial posting
Methods code
cum_gcskewdescriptionprevnextTop
sub cum_gcskew {
    msg_error("WARNING: cum_gcskew is deprecated since v.1.6.13.\n" .
	      "         This method will be removed in future releases.\n" .
	      "         use gcskew(\$gb, -cumulative=>1) instead!\n\n");

    return gcskew(@_, -cumulative=>1);
}
dist_in_ccdescriptionprevnextTop
sub dist_in_cc {
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);
    my $first = shift @args;
    my $second = shift @args;

    $first = $gb->{$first}->{start} if($first =~ /^FEATURE/ || /^CDS/);
    $second = $gb->{$second}->{start} if($second =~ /^FEATURE/ || /^CDS/);

    unless(length($second)){
	my ($ori, $ter) = rep_ori_ter($gb);
	$second = $ori;
    }

    my @dist;

    $dist[0] = abs($first - $second);
    $dist[1] = abs($first + length($gb->{SEQ}) - $second);
    $dist[2] = abs($first - (length($gb->{SEQ}) + $second));
    
    my @new = sort {$a <=> $b} @dist;

    return shift @new;
}
find_ori_terdescriptionprevnextTop
sub find_ori_ter {
    require Statistics::Descriptive;
    &opt_default(output=>"stdout", purine=>0, keto=>0, window=>4096);
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);
    my $len = length($gb->{SEQ});
    my $output = opt_val("output");
    my $purine = opt_val("purine");
    my $keto = opt_val("keto");
    my $lowpass = opt_val("filter");
    my $power = opt_val("window");

    &msg_send("\nfind_ori_ter:\n") if ($output eq 'stdout');

    my ($max, $min);
    if(length $lowpass){
	require Math::FFT;
	my $window = int($len / $power);
my @gcskew = gcskew($gb, -output=>"/dev/null", -window=>$window, -purine=>$purine, -keto=>$keto); while(scalar @gcskew > $power){ pop @gcskew; } my $fft = new Math::FFT([@gcskew]); my $coeff = $fft->rdft(); my $coeff2 = [@{$coeff}]; my $spctrm = $fft->spctrm(); my $j; my $power2 = int($power/100);
$power2 ++ if ($power2 %2 == 1); for($j = $power2 * (100 - $lowpass) - 1; $j < $power; $j ++){ $coeff->[$j] = 0; } my $orig = $fft->invrdft($coeff); my (@cum, $tmp); foreach my $value (@{$orig}){ $tmp += $value; push(@cum, $tmp); } my $stat = Statistics::Descriptive::Full->new(); $stat->add_data(@cum); my $maxi = $stat->maxdex(); my $mini = $stat->mindex(); $max = ($maxi + 1) * $window - int($window/2);
$min = ($mini + 1) * $window - int($window/2);
}else{ local *peak_search = sub{ my $seq = shift; if($purine){ $seq =~ tr/atgcn/02021/; }elsif($keto){ $seq =~ tr/atgcn/20021/; }else{ $seq =~ tr/atgcn/11021/; } my (@data, $val, $i); for($i = 0; $i <= length($seq); $i ++){ if(substr($seq, $i, 1) =~ /^\d$/){ $val += substr($seq, $i, 1) - 1; } push(@data, $val); } my $stat = Statistics::Descriptive::Full->new(); $stat->add_data(@data); return ($stat->maxdex(), $min = $stat->mindex()); }; if($len > 100000){ my @cumgcskew = gcskew($gb, -output=>"/dev/null", -window=>10000, -purine=>$purine, -keto=>$keto, -cumulative=>1); my $stat = Statistics::Descriptive::Full->new(); $stat->add_data(@cumgcskew); my $maxi = $stat->maxdex(); my $mini = $stat->mindex(); ($max, undef) = peak_search(substr($gb->{SEQ}, $maxi * 10000, 20000)); (undef, $min) = peak_search(substr($gb->{SEQ}, $mini * 10000, 20000)); $max += $maxi * 10000; $min += $mini * 10000; $max = 0 if ($max < $len / 1000 || abs($max - $len) < $len / 1000); }else{ ($max, $min) = peak_search($gb->{SEQ}); } } &msg_send(" Predicted Origin: " , $max, "\n") if ($output eq 'stdout'); &msg_send(" Predicted Terminus: " , $min, "\n\n") if ($output eq 'stdout'); return ($max, $min);
}
gcsidescriptionprevnextTop
sub gcsi {
    require Math::FFT;

    opt_default(window=>4096, purine=>0, keto=>0, at=>0, version=>2, p=>0);
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);
    my %opt = opt_val();

    my $window = int(length($gb->{SEQ}) / $opt{'window'});
if($window < 10){ die("Error in gcsi: number of windows is too large, or the genome is too small.\n" . "GCSI would not be accurate for window size less than 100 bp.\n"); } my @gcskew = gcskew($gb, -output=>'/dev/null', -window=>$window, -purine=>$opt{'purine'}, -keto=>$opt{'keto'}, -at=>$opt{'at'}); while(scalar @gcskew > $opt{'window'}){ pop @gcskew; } local *gcsicore = sub{ my @gcskew = @_; my @cumgcskew = cumulative(@gcskew); my $fft = new Math::FFT([@gcskew]); my @spectrum = @{$fft->spctrm()}; shift @spectrum; my $first = shift @spectrum; my $dist = abs(max(@cumgcskew)) + abs(min(@cumgcskew)); my ($gcsi, $sr); if($opt{'version'} == 1){ $sr = $first/mean(@spectrum);
$gcsi = ($sr/6000 + $dist/600)/2;
}else{ $dist *= 4096/$opt{'window'};
$sr = 40 * (($first * 6000 * 100) ** 0.4); $gcsi = sqrt($sr/6000 * $dist/600); } return ($gcsi, $sr, $dist); }; my ($gcsi, $sr, $dist) = gcsicore(@gcskew); if($opt{'p'}){ require Statistics::Distributions; my @random; for (1..100){ my ($rgcsi, undef, undef) = gcsicore(shuffle(@gcskew)); push(@random, $rgcsi); } my $z = abs(($gcsi - mean(@random))/standard_deviation(@random));
my $p = Statistics::Distributions::uprob($z) * 2; # my $rcmd = new Rcmd();
# say $rcmd->normtest(@random);
return ($gcsi, $sr, $dist, $z, $p); } if(wantarray()){ return ($gcsi, $sr, $dist); }else{ return $gcsi; }
}
gcskewdescriptionprevnextTop
sub gcskew {
    &opt_default(window=>10000, at=>0, purine=>0, keto=>0, output=>"show", 
		 filename=>"gcskew.png", cumulative=>0, slide=>undef);
    my @args       = opt_get(@_);
    my $gb         = opt_as_gb(shift @args);
    my $ref        =\$ gb->{SEQ};
    my $len        = length($$ref);
    my $window     = opt_val("window");
    my $slide      = opt_val("slide") || $window;
    die('Error at gcskew(): window size too small') if ($window < 10);
    my $output     = opt_val("output");
    my $cumulative = '';
    $cumulative    = "Cumulative " if (opt_val("cumulative"));
    my $filename   = opt_val("filename");
    $filename      =~ s/\.png$/\.csv/ if (opt_val("output") eq 'f');
    my $at         = opt_val("at");
    my $purine     = opt_val("purine");
    my $keto       = opt_val("keto");
    my @gcskew     = ();
    my @location   = ();
    my ($tmp, $pos, $j, $i) = (0,0,0,0);

    while($len - $pos >= $window){
	my ($g, $c);

	if($at){
	    $g =  substr($$ref, $pos, $window) =~ tr/a/a/;
	    $c =  substr($$ref, $pos, $window) =~ tr/t/t/;
	}elsif($purine){
	    $g =  substr($$ref, $pos, $window) =~ tr/a/a/;
	    $g += substr($$ref, $pos, $window) =~ tr/g/g/;
	    $c =  substr($$ref, $pos, $window) =~ tr/t/t/;
	    $c += substr($$ref, $pos, $window) =~ tr/c/c/;
	}elsif($keto){
	    $g =  substr($$ref, $pos, $window) =~ tr/t/t/;
	    $g += substr($$ref, $pos, $window) =~ tr/g/g/;
	    $c =  substr($$ref, $pos, $window) =~ tr/a/a/;
	    $c += substr($$ref, $pos, $window) =~ tr/c/c/;
	}else{
	    $g =  substr($$ref, $pos, $window) =~ tr/g/g/;
	    $c =  substr($$ref, $pos, $window) =~ tr/c/c/;
	}

	if(length($cumulative)){
	    if ($c+$g <= 0){
		$tmp += 0;
	    }else{
		$tmp += sprintf("%.6f",($c-$g)/($c+$g));
} $gcskew[$i] = $tmp; }else{ if ($c+$g <= 0){ $gcskew[$i] = 0; }else{ $gcskew[$i] = sprintf("%.6f",($c-$g)/($c+$g));
} } $location[$i] = $pos; $pos += $slide; $i ++; } $i --; my $title = $cumulative . "GC skew"; if ($at){ $title = $cumulative . "AT skew"; }elsif($purine){ $title = $cumulative . "Purine skew"; }elsif($keto){ $title = $cumulative . "Keto skew"; } if ($output eq 'g' || $output eq 'show'){ mkdir ("graph", 0777); _UniMultiGrapher(\@ location,\@gcskew, -x=>"bp", -y=>$title, -filename=>$filename, -title=>$title, -style=>"lines", -type=>"columns", ); msg_gimv("graph/" . $filename) if ($output eq 'show'); }elsif ($output eq 'f'){ my $j = 0; mkdir ("data", 0777); open(OUT, ">data/" . $filename); print OUT "location,$title\n"; for ($j = 0; $j <= $i; $j++){ print OUT $location[$j], ",", $gcskew[$j], "\n"; } close(OUT); } return @gcskew;
}
gcwindescriptionprevnextTop
sub gcwin {
    &opt_default(window=>10000, at=>0, purine=>0, keto=>0, output=>"show", 
		 application=>"gimv", filename=>"gcwin.png", skipGap=>0);
    my @args = opt_get(@_);

    my $gb = opt_as_gb(shift @args);
    my $ref =\$ gb->{SEQ};
    my $window = opt_val("window");
    my $at = opt_val("at");
    my $purine = opt_val("purine");
    my $keto = opt_val("keto");
    my $skip = opt_val("skipGap");
    my $application = opt_val("application");
    my $filename = opt_val("filename");
    $filename =~ s/\.png$/\.csv/ if (opt_val("output") eq 'f');
    my $opt = opt_val("output");
    my (@gcwin, @location);
    my $j;
    
    my $i = 0;
    my ($g, $c, $rest);
    while(length($$ref) - ($window * $i) >= $window){
        if($at){
            $g = substr($$ref, $window * $i, $window) =~ tr/a/a/;
            $c = substr($$ref, $window * $i, $window) =~ tr/t/t/;
	    $rest =  substr($$ref, $window * $i, $window) =~ tr/g/g/;
	    $rest += substr($$ref, $window * $i, $window) =~ tr/c/c/;
        }elsif($purine){
            $g = substr($$ref, $window * $i, $window) =~ tr/g/g/;
            $c = substr($$ref, $window * $i, $window) =~ tr/a/a/;
	    $rest =  substr($$ref, $window * $i, $window) =~ tr/t/t/;
	    $rest += substr($$ref, $window * $i, $window) =~ tr/c/c/;
        }elsif($keto){
            $g = substr($$ref, $window * $i, $window) =~ tr/g/g/;
            $c = substr($$ref, $window * $i, $window) =~ tr/t/t/;
	    $rest =  substr($$ref, $window * $i, $window) =~ tr/a/a/;
	    $rest += substr($$ref, $window * $i, $window) =~ tr/c/c/;
	}else{
            $g = substr($$ref, $window * $i, $window) =~ tr/g/g/;
            $c = substr($$ref, $window * $i, $window) =~ tr/c/c/;
	    $rest =  substr($$ref, $window * $i, $window) =~ tr/a/a/;
	    $rest += substr($$ref, $window * $i, $window) =~ tr/t/t/;
        }
	$rest += $g + $c;

	if($rest == 0 && $skip){
	    $gcwin[$i] = $gcwin[$i - 1];
	}else{
	    $gcwin[$i] = $rest >= 1 ? sprintf("%.6f",($g+$c)/$rest) : 0;
} $location[$i] = $i * $window; $i ++; } $i --; my $title = "GC content"; if ($at){ $title = "AT content"; }elsif($purine){ $title = "Purine content"; }elsif($keto){ $title = "Keto content"; } if ($opt eq 'g' || $opt eq 'show'){ mkdir ("graph", 0777); _UniMultiGrapher(\@ location,\@ gcwin, -x=>"bp", -y=>$title, -filename=>$filename, -title=>$title, -style=>"lines", -type=>"columns" ); msg_gimv("graph/" . $filename) if ($opt eq 'show');; }elsif ($opt eq 'f'){ my $j = 0; mkdir ("data", 0777); open(OUT, ">data/" . $filename); print OUT "location,$title\n"; for ($j = 0; $j <= $i; $j++){ print OUT $location[$j], ",", $gcwin[$j], "\n"; } close(OUT); } return @gcwin;
}
genes_from_oridescriptionprevnextTop
sub genes_from_ori {
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);
    my $wing = shift @args;

    my ($ori, $ter) = rep_ori_ter($gb);

    my (@sectionA, @sectionB, @sectionC, @left, @right);
    
    if($ori < $ter){
	foreach my $cds ($gb->cds()){

	    if($gb->{$cds}->{start} <= $ori){
		push(@sectionA, $cds);
	    }elsif($gb->{$cds}->{start} >= $ori && $gb->{$cds}->{start} <= $ter){
		push(@sectionB, $cds);
	    }elsif($gb->{$cds}->{start} >= $ter){
		push(@sectionC, $cds);
	    }else{
		warn("Something is wrong at G::Seq::GCskew::genes_from_ori()");
	    }
	}

	@left = (reverse(@sectionA), reverse(@sectionC));
	@right = @sectionB;

    }else{
	foreach my $cds ($gb->cds()){

	    if($gb->{$cds}->{start} < $ter){
		push(@sectionA, $cds);
	    }elsif($gb->{$cds}->{start} >= $ter && $gb->{$cds}->{start} <= $ori){
		push(@sectionB, $cds);
	    }elsif($gb->{$cds}->{start} >= $ori){
		push(@sectionC, $cds);
	    }else{
		warn("Something is wrong at G::Seq::GCskew::genes_from_ori()");
	    }
	}
	
	@left = (reverse(@sectionB));
	@right = (@sectionC, @sectionA);
	
    }

    if(lc($wing) =~ /l/){
	return @left;
    }elsif(lc($wing) =~ /r/){
	return @right;
    }else{
	my %hash;
	foreach my $cds ($gb->cds()){
	    $hash{$cds} = dist_in_cc($gb, $gb->{$cds}->{start});
	}

	my @all = sort{ $hash{$a} <=> $hash{$b}} keys %hash;
	return @all;
    }
}
genomicskewdescriptionprevnextTop
sub genomicskew {
    &opt_default(divide=>250, at=>0, output=>"show", application=>"gimv",
		  filename=>"genomicskew.png", intron=>0);
    my @args = opt_get(@_);

    my $filename = opt_val("filename");
    $filename =~ s/\.png$/\.csv/ if (opt_val("output") eq 'f');
	
    my $gb = opt_as_gb(shift @args);
    my $divide = opt_val("divide");
    my $opt = opt_val("output");
    my $application = opt_val("application");
    my $at = opt_val("at");
    my $intron = opt_val("intron");
    my (@gcskew, @betskew, @geneskew, @thirdskew);
    my @location = (0..$divide);
    my ($j, $window, $CDS, $BET, $THIRD);

    foreach my $cds ($gb->cds()){
	next if (length $gb->{$cds}->{join});
	my $seq .= $gb->get_gbkseq($gb->{$cds}->{start}, $gb->{$cds}->{end});
	$CDS .= $seq;
       
        for($j = 2; $j <= length($seq); $j += 3){
            if ($gb->{"$cds"}->{direction} eq 'complement'){
                $THIRD .= substr($seq, $j, 1);
            }else{
                $THIRD .= substr($seq, $j - 2, 1);
            }
        }
    }

    foreach my $cds ($gb->intergenic()){
	$BET .= $gb->get_geneseq($cds);
    }

    my $i = 0;
    
    $window = int(length($gb->{SEQ}) / $divide);
while($i <= $divide){ my $g = substr($gb->{SEQ}, $window * $i, $window) =~ tr/g/g/; $g = substr($gb->{SEQ}, $window * $i, $window) =~ tr/a/a/ if ($at); my $c = substr($gb->{SEQ}, $window * $i, $window) =~ tr/c/c/; $c = substr($gb->{SEQ}, $window * $i, $window) =~ tr/t/t/ if ($at); $gcskew[$i] = 0; $gcskew[$i] = sprintf("%.6f",($c-$g)/($c+$g)) unless ($c+$g<1);
$i ++; } $i = 0; $window = int(length($CDS) / $divide);
while($i <= $divide){ my $g = substr($CDS, $window * $i, $window) =~ tr/g/g/; $g = substr($CDS, $window * $i, $window) =~ tr/a/a/ if ($at); my $c = substr($CDS, $window * $i, $window) =~ tr/c/c/; $c = substr($CDS, $window * $i, $window) =~ tr/t/t/ if ($at); $geneskew[$i] = 0; $geneskew[$i] = sprintf("%.6f",($c-$g)/($c+$g)) unless ($c+$g<1);
$i ++; } $i = 0; $window = int(length($BET) / $divide);
while($i <= $divide){ my $g = substr($BET, $window * $i, $window) =~ tr/g/g/; $g = substr($BET, $window * $i, $window) =~ tr/a/a/ if ($at); my $c = substr($BET, $window * $i, $window) =~ tr/c/c/; $c = substr($BET, $window * $i, $window) =~ tr/t/t/ if ($at); $betskew[$i] = 0; $betskew[$i] = sprintf("%.6f",($c-$g)/($c+$g)) unless ($c+$g<1);
$i ++; } $i = 0; $window = int(length($THIRD) / $divide);
while($i <= $divide){ my $g = substr($THIRD, $window * $i, $window) =~ tr/g/g/; $g = substr($THIRD, $window * $i, $window) =~ tr/a/a/ if ($at); my $c = substr($THIRD, $window * $i, $window) =~ tr/c/c/; $c = substr($THIRD, $window * $i, $window) =~ tr/t/t/ if ($at); $thirdskew[$i] = 0; $thirdskew[$i] = sprintf("%.6f",($c-$g)/($c+$g)) unless ($c+$g<1);
$i ++; } my $title = "GC skew"; $title = "AT skew" if ($at); if ($opt eq "show" || $opt eq "g"){ mkdir ("graph", 0777); _UniMultiGrapher(\@ location, -x=>"bp", -y=>$title,\@ gcskew, -x1=>"whole genome",\@ geneskew, -x2=>"coding region",\@ betskew, -x3=>"intergenic region",\@ thirdskew, -x4=>"codon third position", -style=>"lines", -type=>"columns", -filename=>$filename, -title=>$title ); msg_gimv("graph/" . $filename) if ($opt eq 'show'); }elsif ($opt eq 'f'){ my $j = 0; mkdir ("data", 0777); open(OUT, ">data/" . $filename); print OUT "location,$title,coding,intergenic,third codon\n"; for ($j = 0; $j <= $divide; $j++){ print OUT $location[$j], ",", $gcskew[$j], ",", $geneskew[$j], ",", $betskew[$j], ",", $thirdskew[$j], ",", "\n"; } close(OUT); } return (\@gcskew,\@ geneskew,\@ betskew,\@ thirdskew);
}
leading_stranddescriptionprevnextTop
sub leading_strand {
    my @args = opt_get(@_);
    my $gb = shift @args;
    my ($ori, $ter) = rep_ori_ter($gb);
    my ($seq1, $seq2);

    if ($ori > $ter){
	$seq1  = substr($gb->{SEQ}, $ori);
	$seq1 .= substr($gb->{SEQ}, 0, $ter);
	$seq2  = complement(substr($gb->{SEQ}, $ter, $ori - $ter));
    }else{
	$seq1 = substr($gb->{SEQ}, $ori, $ter - $ori);
	$seq2 = complement( substr($gb->{SEQ}, $ter) . substr($gb->{SEQ}, 0, $ori) );
    }
    
    if(wantarray()){
	return ($seq1, $seq2);
    }else{
	return $seq1 . $seq2;
    }
}
query_armdescriptionprevnextTop
sub query_arm {
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);
    my $pos = shift @args;

    if($pos =~ /^FEATURE/ || /^CDS/){
	$pos = $gb->{$pos}->{start};
    }
    
    my ($ori, $ter) = rep_ori_ter($gb);

    if($ori < $ter){
	if($pos <= $ori){
	    return 'left';
	}elsif($pos >= $ori && $pos <= $ter){
	    return 'right';
	}elsif($pos >= $ter){
	    return 'left';
	}
    }else{
	if($pos < $ter){
	    return 'right';
	}elsif($pos >= $ter && $pos <= $ori){
	    return 'left';
	}elsif($pos >= $ori){
	    return 'right';
	}
    }
}
query_stranddescriptionprevnextTop
sub query_strand {
    opt_default(direction=>'direct');
    my @args = opt_get(@_);
    my $gb = shift @args;
    my $pos = shift @args;
    my $direction = opt_val("direction");

    if($pos =~ /^FEATURE/ || /^CDS/){
	$direction = $gb->{$pos}->{direction};
	$pos = $gb->{$pos}->{start};
    }

    my ($ori, $ter) = rep_ori_ter($gb);

    if ($ori > $ter){
	if ($pos < $ter || $pos > $ori){
	    if ($direction eq 'complement'){
		return ("lagging");
	    }else{
		return ("leading");
	    }
	}else{
	    if ($direction eq 'complement'){
		return ("leading");
	    }else{
		return ("lagging");
	    }
	}
    }else{
	if ($pos > $ori && $pos < $ter){
	    if ($direction eq 'complement'){
		return ("lagging");
	    }else{
		return ("leading");
	    }
	}else{
	    if ($direction eq 'complement'){
		return ("leading");
	    }else{
		return ("lagging");
	    }
	}
    }
}
rep_ori_terdescriptionprevnextTop
sub rep_ori_ter {
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);
    my ($ori, $ter);
    my $id = $gb->{LOCUS}->{id};


    if(length $gb->{FEATURE0}->{terminus}){
	$ori = $gb->{FEATURE0}->{origin};
	$ter = $gb->{FEATURE0}->{terminus};
    }else{

	if ($id eq 'U00096' || $id eq 'NC_000913'){
	    $ori = 3923500 - 1; 
	    $ter = 1588800 - 1; 
	}elsif ($id eq 'AL009126' || $id eq 'NC_000964'){
	    $ori = 1 - 1;
	    $ter = 2017000 - 1;
	}elsif ($id eq 'L42023' || $id eq 'NC_000907'){
	    $ori = 603000 - 1;
	    $ter = 1518000 - 1;
	}elsif ($id eq 'AL513382' || $id eq 'NC_003198'){
	    $ori = 3765000 - 1;
	    $ter = 1437000 - 1;
	}else{
	    msg_error('Using find_ori_ter() to predict...' . "\n");
	    ($ori, $ter) = &G::Seq::GCskew::find_ori_ter($gb, -output=>"/dev/null");
	}

	my $interface = msg_ask_interface();
	msg_interface('NULL');
	my $cds = ($gb->find(-type=>'rep_origin'))[0];
	if($cds){
	    $ori = int(($gb->{$cds}->{end} + $gb->{$cds}->{start})/2) - 1;
msg_error("rep_origin feature found. Using $ori as origin.\n"); } msg_interface($interface); $gb->{FEATURE0}->{origin} = $ori; $gb->{FEATURE0}->{terminus} = $ter; } return ($ori, $ter);
}
set_gc3descriptionprevnextTop
sub set_gc3 {
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);

    foreach my $cds ($gb->cds()){
	my $geneseq = $gb->get_geneseq($cds);

	my (%gc3, $tot);

	my $i = 0;
	for($i = 2; $i < length $geneseq; $i += 3){
	    $gc3{substr($geneseq, $i, 1)}++;
	    $tot ++;
	}

	$gb->{$cds}->{gc3} = ($gc3{g} + $gc3{c})/$tot;
} return 1;
}
set_stranddescriptionprevnextTop
sub set_strand {
    my @args = opt_get(@_);
    my $gb = opt_as_gb(shift @args);

    foreach my $cds ($gb->cds()){
	$gb->{$cds}->{strand} = query_strand($gb, $cds);
	$gb->{$cds}->{arm} = query_arm($gb, $cds);
    }

    return 1;
}
General documentation
No general documentation available.