| 1 | #!/usr/bin/perl |
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| 2 | |
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| 3 | ########################################################################### |
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| 4 | # Purpose: To calculate the correlation of two sets of scores in one file. |
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| 5 | # Usage: correlation.pl infile.bed output.txt column1 column2 |
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| 6 | # (column start from 1) |
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| 7 | # Written by: Yi Zhang (June, 2005) |
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| 8 | ########################################################################### |
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| 9 | if (!$ARGV[0] || !$ARGV[1] || !defined($ARGV[2]) || !defined($ARGV[3]) ) { |
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| 10 | print STDERR "Usage: correlation.pl infile.bed output.txt column1 column2\n"; |
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| 11 | print STDERR " (column start from 1)\n"; |
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| 12 | exit; |
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| 13 | } |
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| 14 | my $file = $ARGV[0]; |
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| 15 | my $out = $ARGV[1]; |
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| 16 | |
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| 17 | die "<font color=\"yellow\">The input columns contain numerical values: $ARGV[2], $ARGV[3]</font>.\n" if ($ARGV[2] =~ /[a-zA-Z]+/ || $ARGV[3] =~ /[a-zA-Z]+/); |
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| 18 | |
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| 19 | my $col1 = $ARGV[2] - 1; |
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| 20 | my $col2 = $ARGV[3] - 1; |
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| 21 | |
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| 22 | my ($f, $o); |
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| 23 | my (@a, @b); |
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| 24 | |
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| 25 | my $n_t = 0; |
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| 26 | open($f, $file) or die "Could't open $file, $!\n"; |
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| 27 | while(<$f>) { |
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| 28 | chomp; |
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| 29 | my @t = split(/\t/); |
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| 30 | if ($n_t == 0) { |
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| 31 | $n_t = scalar(@t) - 1; |
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| 32 | die "<font color=\"yellow\">The input column number exceeds the size of the file: $col1, $col2, $n_t</font>\n" if ( $col1 > $n_t || $col2 > $n_t ); |
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| 33 | } |
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| 34 | die "<font color=\"yellow\">The columns you have selected contain non numeric characters:$t[$col1] and $t[$col2] \n</font>" if ($t[$col1] =~ /[a-zA-Z]+/ || $t[$col2] =~ /[a-zA-Z]+/); |
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| 35 | push(@a, $t[$col1]); |
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| 36 | push(@b, $t[$col2]); |
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| 37 | } |
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| 38 | close($f); |
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| 39 | |
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| 40 | my $result = correlation(\@a, \@b); |
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| 41 | |
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| 42 | open($o, ">$out") or die "Couldn't open $out, $!\n"; |
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| 43 | $col1 = $col1 + 1; |
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| 44 | $col2 = $col2 + 1; |
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| 45 | print $o "The correlation of column $col1 and $col2 is $result\n"; |
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| 46 | close($o); |
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| 47 | print "The correlation of column $col1 and $col2 is $result\n"; |
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| 48 | |
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| 49 | sub correlation { |
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| 50 | my ($array1ref, $array2ref) = @_; |
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| 51 | my ($sum1, $sum2); |
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| 52 | my ($sum1_squared, $sum2_squared); |
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| 53 | foreach (@$array1ref) { $sum1 += $_; $sum1_squared += $_**2; } |
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| 54 | foreach (@$array2ref) { $sum2 += $_; $sum2_squared += $_**2; } |
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| 55 | my $numerator = (@$array1ref**2) * covariance($array1ref, $array2ref); |
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| 56 | my $denominator = sqrt(((@$array1ref * $sum1_squared) - ($sum1**2)) * |
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| 57 | ((@$array1ref * $sum2_squared) - ($sum2**2))); |
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| 58 | my $r; |
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| 59 | if ($denominator == 0) { |
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| 60 | print STDERR "The denominator is 0.\n"; |
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| 61 | exit 0; |
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| 62 | } else { |
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| 63 | $r = $numerator / $denominator; |
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| 64 | } |
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| 65 | return $r; |
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| 66 | } |
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| 67 | |
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| 68 | sub covariance { |
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| 69 | my ($array1ref, $array2ref) = @_; |
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| 70 | my ($i, $result); |
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| 71 | for ($i = 0; $i < @$array1ref; $i++) { |
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| 72 | $result += $array1ref->[$i] * $array2ref->[$i]; |
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| 73 | } |
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| 74 | $result /= @$array1ref; |
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| 75 | $result -= mean($array1ref) * mean($array2ref); |
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| 76 | } |
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| 77 | |
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| 78 | sub mean { |
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| 79 | my ($arrayref) = @_; |
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| 80 | my $result; |
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| 81 | foreach (@$arrayref) { $result += $_; } |
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| 82 | return $result/@$arrayref; |
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| 83 | } |
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| 84 | |
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