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view bam2cfg.pl @ 14:2dd38b423eae draft
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author | jeremie |
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date | Fri, 27 Jun 2014 08:42:21 -0400 |
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#!/opt/local/bin/perl #Create a BreakDancer configuration file from a set of bam files use strict; use warnings; use Getopt::Std; use Statistics::Descriptive; use GD::Graph::histogram; use FindBin qw($Bin); use lib "$FindBin::Bin"; #use lib '/gscuser/kchen/1000genomes/analysis/scripts/'; use AlnParser; my %opts = (q=>35, n=>10000, v=>1, c=>4, b=>50, s=>50); getopts('q:n:c:b:p:hmf:gCv:', \%opts); die(" Usage: bam2cfg.pl <bam files> Options: -q INT Minimum mapping quality [$opts{q}] -m Using mapping quality instead of alternative mapping quality -s Minimal mean insert size [$opts{s}] -C Change default system from Illumina to SOLiD -c FLOAT Cutoff in unit of standard deviation [$opts{c}] -n INT Number of observation required to estimate mean and s.d. insert size [$opts{n}] -v FLOAT Cutoff on coefficients of variation [$opts{v}] -f STRING A two column tab-delimited text file (RG, LIB) specify the RG=>LIB mapping, useful when BAM header is incomplete -b INT Number of bins in the histogram [$opts{b}] -g Output mapping flag distribution -h Plot insert size histogram for each BAM library \n ") unless (@ARGV); my $AP=new AlnParser(platform=>$opts{C}); my %cRGlib; my %clibs; if($opts{f}){ open(RGLIB,"<$opts{f}") || die "unable to open $opts{f}\n"; while(<RGLIB>){ chomp; my ($rg,$lib)=split; $clibs{$lib}=1; $cRGlib{$rg}=$lib; } } foreach my $fbam(@ARGV){ my %RGlib; my %RGplatform; my %libs; my %insert_stat; my %readlen_stat; my %libpos; my %flagHgram; my $recordcounter=0; my $expected_max; if(defined $opts{f}){ %RGlib=%cRGlib; %libs=%clibs; } my $ppos=0; open(BAM,"samtools view -h $fbam |") || die "unable to open $fbam\n"; while(<BAM>){ chomp; if(/^\@RG/){ #getting RG=>LIB mapping from the bam header my ($id)=($_=~/ID\:(\S+)/); my ($lib)=($_=~/LB\:(\S+)/); my ($platform)=($_=~/PL\:(\S+)/); my ($sample)=($_=~/SM\:(\S+)/); my ($insertsize)=($_=~/PI\:(\d+)/); #if(defined $insertsize && $insertsize>0){ #$lib=$sample . '_'. $lib; $libs{$lib}=1; $RGlib{$id}=$lib; $RGplatform{$id}=$platform; #} } else{ next if(/^\@/); my @libas=keys %libs; my @selected_libs=keys %insert_stat; if($#libas<0){ if($#selected_libs>=0){ last; } else{ $libs{'NA'}=1; $RGlib{'NA'}='NA'; $RGplatform{'NA'}=($opts{C})?'solid':'illumina'; } } if(!defined $expected_max || $expected_max<=0){ $expected_max=3*($#libas+1)*$opts{n}; } last if($recordcounter>$expected_max); my $t=$AP->in($_,'sam',\%RGplatform,$opts{m}); #die "Please sort bam by position\n" if($t->{pos}<$ppos); next if($t->{pos}<$ppos); $ppos=$t->{pos}; my $lib; if(defined $t->{readgroup}){ if(defined $RGlib{$t->{readgroup}}){ $lib=$RGlib{$t->{readgroup}}; } else{ $lib=$t->{readgroup}; $libs{$t->{readgroup}}=1; $RGlib{$t->{readgroup}}=$t->{readgroup}; } } else{ $lib='NA'; } #my $lib=($t->{readgroup})?$RGlib{$t->{readgroup}}:'NA'; #when multiple libraries are in a BAM file next unless(defined $lib && $libs{$lib}); $readlen_stat{$lib}=Statistics::Descriptive::Full->new() if(!defined $readlen_stat{$lib}); $readlen_stat{$lib}->add_data($t->{readlen}); next if ($t->{qual}<=$opts{q}); #skip low quality mapped reads $recordcounter++; $libpos{$lib}++; if(defined $t->{readgroup}){ $flagHgram{$t->{readgroup}}{$t->{flag}}++; $flagHgram{$t->{readgroup}}{all}++; } my $nreads=(defined $insert_stat{$lib})?$insert_stat{$lib}->count():1; if($nreads/$libpos{$lib}<1e-4){ #single-end lane delete $libs{$lib}; delete $insert_stat{$lib}; } next unless(($t->{flag}==18 || $t->{flag}==20) && $t->{dist}>=0); $insert_stat{$lib}=Statistics::Descriptive::Full->new() if(!defined $insert_stat{$lib}); $insert_stat{$lib}->add_data($t->{dist}); if($insert_stat{$lib}->count()>$opts{n}){ delete $libs{$lib}; } } } close(BAM); my %stdms; my %stdps; foreach my $lib(keys %insert_stat){ my $readlen=$readlen_stat{$lib}->mean(); my @isize=$insert_stat{$lib}->get_data(); my $mean=$insert_stat{$lib}->mean(); my $std=$insert_stat{$lib}->standard_deviation(); delete $insert_stat{$lib}; my $insertsize=Statistics::Descriptive::Full->new(); foreach my $x(@isize){ next if($x>$mean+5*$std); $insertsize->add_data($x); } $mean=$insertsize->mean(); $std=$insertsize->standard_deviation(); next if($mean<$opts{s}); my $cv=$std/$mean; if($cv>=$opts{v}){ print STDERR "Coefficient of variation $cv in library $lib is larger than the cutoff $opts{v}, poor quality data, excluding from further analysis.\n"; next; } my $num=$insertsize->count(); next if($num<100); my ($stdm,$stdp)=(0,0); my ($nstdm,$nstdp)=(0,0); foreach my $x($insertsize->get_data()){ if($x>$mean){ $stdp+=($x-$mean)**2; $nstdp++; } else{ $stdm+=($x-$mean)**2; $nstdm++; } } $stdm=sqrt($stdm/($nstdm-1)); $stdp=sqrt($stdp/($nstdp-1)); $stdms{$lib}=$stdm; $stdps{$lib}=$stdp; $insert_stat{$lib}=$insertsize; } foreach my $rg(keys %RGlib){ my $lib=$RGlib{$rg}; my $platform=$RGplatform{$rg} || 'illumina'; #default illumina next unless($insert_stat{$lib}); my $readlen=$readlen_stat{$lib}->mean(); my $mean=$insert_stat{$lib}->mean(); my $std=$insert_stat{$lib}->standard_deviation(); my $num=$insert_stat{$lib}->count(); my $upper=$mean+$opts{c}*$stdps{$lib} if(defined $opts{c}); my $lower=$mean-$opts{c}*$stdms{$lib} if(defined $opts{c}); $lower=0 if(defined $lower && $lower<0); printf "readgroup\:%s\tplatform:%s\tmap\:%s\treadlen\:%.2f\tlib\:%s\tnum:%d",$rg,$platform,$fbam,$readlen,$lib,$num; printf "\tlower\:%.2f\tupper\:%.2f",$lower,$upper if(defined $upper && defined $lower); printf "\tmean\:%.2f\tstd\:%.2f",$mean,$std; # compute the normality my @data=$insert_stat{$lib}->get_data(); my $n_data = @data; @data = sort {$a <=> $b} @data; my $n_data_ = @data; my $p_value = ShapiroWilk(\@data); if($p_value>0) { my $log_p_value = log($p_value)/log(10); printf "\tSWnormality\:%.2f",$log_p_value; } elsif($p_value == -1) { printf "\tSWnormality\:data not qualified -1"; } elsif($p_value == -2.1){ printf "\tSWnormality\:data not qualified -2.1"; } elsif($p_value == -2.2){ printf "\tSWnormality\:data not qualified -2.2"; } elsif($p_value == -2.3){ printf "\tSWnormality\:data not qualified -2.3"; } elsif($p_value == 0) { printf "\tSWnormality\:minus infinity"; } if($opts{g}){ printf "\tflag:"; foreach my $f(sort keys %{$flagHgram{$rg}}){ next if($f eq 'all'); printf "%d(%.2f%%)",$f,($flagHgram{$rg}{$f} || 0)*100/$flagHgram{$rg}{all}; } printf "%d",$flagHgram{$rg}{all}; } printf "\texe:samtools view\n"; } if($opts{h}){ # plot insert size histogram for each library foreach my $lib(keys %insert_stat){ my $graph = new GD::Graph::histogram(1000,600); my $library="$fbam.$lib"; $graph->set( x_label => 'Insert Size (bp)', y_label => 'Count', title => $library, x_labels_vertical => 1, bar_spacing => 0, shadow_depth => 1, shadowclr => 'dred', transparent => 0, histogram_bins => $opts{b}, ) or warn $graph->error; my @data=$insert_stat{$lib}->get_data(); my $gd = $graph->plot(\@data) or die $graph->error; $library=~s/.*\///g; my $imagefile="$library.insertsize_histogram.png"; open(IMG, ">$imagefile") or die $!; binmode IMG; print IMG $gd->png; my $datafile="$library.insertsize_histogram"; open(OUT,">$datafile"); foreach my $x(@data){ print OUT "$x\n"; } close(OUT); } } } ###################################################### Shapiro Wilk Normality test (including functions ppnd, alnorm, poly, min, sign and asin) ######################################################### sub ShapiroWilk { # read input my ($x) = @_; my $n=@$x; my $w = 0; my $ifault = 2; my $init = 0; my $n2 = $n/2; my @a; my $n1 = $n; my $upper = 1; my @c1 = (0.0, 0.221157, -0.147981, -2.07119, 4.434685, -2.706056); my @c2 = (0.0, 0.042981, -0.293762, -1.752461, 5.682633, -3.582633); my @c3 = (0.5440, -0.39978, 0.025054, -0.6714*(10**(-3))); my @c4 = (1.3822, -0.77857, 0.062767, -0.0020322); my @c5 = (-1.5861, -0.31082, -0.083751, 0.0038915); my @c6 = (-0.4803, -0.082676, 0.0030302); my @c7 = (0.164, 0.533); my @c8 = (0.1736, 0.315); my @c9 = (0.256, -0.00635); my @g = (-2.273, 0.459); my $z90 = 1.2816; my $z95 = 1.6449; my $z99 = 2.3263; my $zm = 1.7509; my $zss = 0.56268; my $bf1 = 0.8378; my $xx90 = 0.556; my $xx95 = 0.622; my $zero = 0.0; my $one = 1.0; my $two = 2.0; my $three = 3.0; my $sqrth = 0.70711; my $qtr = 0.25; my $th = 0.375; my $small = 1*(10**(-19)); my $pi6 = 1.909859; my $stqr = 1.047198; my $summ2; my $ssumm2; my $fac; my $rsn; my $an; my $an25; my $a1; my $a2; my $delta; my $range; my $sa; my $sx; my $ssx; my $ssa; my $sax; my $asa; my $xsx; my $ssassx; my $w1; my $y; my $xx; my $xi; my $gamma; my $m; my $s; my $ld; my $bf; my $z90f; my $z95f; my $z99f; my $zfm; my $zsd; my $zbar; my $ncens; my $nn2; my $i; my $i1; my $j; my $pw = $one; if($w >= $zero) {$w = $one;} $an = $n; $ifault = 3; $nn2 = $n/2; if($n2 < $nn2) {return (-1);} $ifault = 1; if($n < 3) {return (-1);} # If INIT is false, calculates coefficients for the test if(!$init){ if($n == 3) { $a[1-1] = $sqrth;} else { $an25 = $an + $qtr; $summ2 = $zero; for(my $i = 1; $i <= $n2; $i++){ ($a[$i-1], $ifault) = ppnd(($i - $th)/$an25); my $a_val = $a[$i-1]; $summ2 = $summ2 + $a[$i-1] ** 2; } $summ2 = $summ2 * $two; $ssumm2 = $summ2 ** 0.5; $rsn = $one / ($an ** 0.5); my $poly_result = poly_(\@c1, 6, $rsn); $a1 = $poly_result - $a[1-1] / $ssumm2; # Normalize coefficients if($n > 5) { $i1 = 3; $a2 = -$a[2-1]/$ssumm2 + poly_(\@c2, 6, $rsn); my $a_val1_new = $a[1-1]; my $a_val2_new = $a[2-1]; my $temp1 = $summ2 - $two * $a[1-1] ** 2 - $two * $a[2-1] ** 2; my $temp2 = $one - $two * $a1 ** 2 - $two * $a2 ** 2; $fac = (($summ2 - $two * $a[1-1] ** 2 - $two * $a[2-1] ** 2)/($one - $two * $a1 ** 2 - $two * $a2 ** 2)) ** 0.5; $a[1-1] = $a1; $a[2-1] = $a2; } else { $i1 = 2; $fac = (($summ2 - $two * $a[1-1] ** 2)/ ($one - $two * $a1 ** 2)) ** 0.5; $a[1-1] = $a1; } for($i = $i1; $i <= $nn2; $i++){ $a[$i-1] = -$a[$i-1]/$fac; my $a_val = $a[$i-1]; } for($i = 1; $i <= $nn2; $i++){ my $a_value = $a[$i-1]; } } $init = 1; } if($n1 < 3) {return (-1);} $ncens = $n - $n1; $ifault = 4; if($ncens < 0 || ($ncens > 0 && $n < 20)) {return (-1);} $ifault = 5; $delta = $ncens/$an; if($delta > 0.8) {return (-2.1);} # If W input as negative, calculate significance level of -W if($w < $zero) { $w1 = $one + $w; $ifault = 0; } else{ # Check for zero range $ifault = 6; $range = @$x[$n1-1] - @$x[1-1]; if($range < $small) {return (-2.2);} # Check for correct sort order on range - scaled X $ifault = 7; $xx = @$x[1-1]/$range; $sx = $xx; $sa = -$a[1-1]; $j = $n - 1; for($i = 2; $i <= $n1; $i++){ $xi = @$x[$i-1]/$range; if($xx-$xi > $small){ return (-2.3); } $sx = $sx + $xi; if($i != $j) { my $sign_value = sign($i - $j); my $min_value = $a[min($i, $j)-1]; my $min_ = min($i, $j); $sa = $sa + sign($i - $j) * $a[min($i, $j)-1]; } $xx = $xi; $j = $j - 1; } $ifault = 0; if($n > 5000) {$ifault = 2}; # Calculate W statistic as squared correlation between data and coefficients $sa = $sa/$n1; $sx = $sx/$n1; $ssa = $zero; $ssx = $zero; $sax = $zero; $j = $n; for($i = 1; $i <= $n1; $i ++){ if($i != $j) { my $sign_result = sign($i - $j); my $min_result = min($i, $j); $asa = sign($i - $j) * $a[min($i, $j)-1] - $sa; } else { $asa = -$sa; } $xsx = @$x[$i-1]/$range - $sx; $ssa = $ssa + $asa * $asa; $ssx = $ssx + $xsx * $xsx; $sax = $sax + $asa * $xsx; $j = $j - 1; } # W1 equals (1-W) claculated to avoid excessive rounding error for W very near 1 (a potential problem in very large samples) $ssassx = ($ssa * $ssx) ** 0.5; $w1 = ($ssassx - $sax) * ($ssassx + $sax)/($ssa * $ssx); } $w = $one - $w1; # Calculate significance level for W (exact for N=3) if($n == 3){ $pw = $pi6 * (asin($w**0.5) - $stqr); return ($pw); } $y = log($w1); $xx = log($an); $m = $zero; $s = $one; if($n <= 11){ $gamma = poly_(\@g, 2, $an); if($y >= $gamma){ $pw = $small; return ($pw); } $y = -log($gamma - $y); $m = poly_(\@c3, 4, $an); $s = exp(poly_(\@c4, 4, $an)) } else{ $m = poly_(\@c5, 4, $xx); $s = exp(poly_(\@c6, 3, $xx)); } if($ncens > 0){ # Censoring by proportion NCENS/N. Calculate mean and sd of normal equivalent deviate of W. $ld = -log($delta); $bf = $one + $xx * $bf1; $z90f = $z90 + $bf * poly_(\@c7, 2, $xx90 ** $xx) ** $ld; $z95f = $z95 + $bf * poly_(\@c8, 2, $xx95 ** $xx) ** $ld; $z99f = $z99 + $bf * poly_(\@c9, 2, $xx) ** $ld; # Regress Z90F,...,Z99F on normal deviates Z90,...,Z99 to get pseudo-mean and pseudo-sd of z as the slope and intercept $zfm = ($z90f + $z95f + $z99f)/$three; $zsd = ($z90*($z90f-$zfm)+$z95*($z95f-$zfm)+$z99*($z99f-$zfm))/$zss; $zbar = $zfm - $zsd * $zm; $m = $m + $zbar * $s; $s = $s * $zsd; } $pw = alnorm(($y - $m)/$s, $upper); return ($pw); } ############################################### ppnd function############################################################ sub ppnd { # read input my ($p) = @_; # define output my $ifault; my $normal_dev; # Local variables my $zero = 0.0; my $one = 1.0; my $half = 0.5; my $split1 = 0.425; my $split2 = 5.0; my $const1 = 0.180625; my $const2 = 1.6; my $q; my $r; # Coefficients for P close to 0.5 my $a0 = 3.3871327179; my $a1 = 5.0434271938*10; my $a2 = 1.5929113202*10**2; my $a3 = 5.9109374720*10; my $b1 = 1.7895169469*10; my $b2 = 7.8757757664*10; my $b3 = 6.7187563600*10; # HASH SUM AB 32.3184577772 # Coefficients for P not close to 0, 0.5 or 1. my $c0 = 1.4234372777; my $c1 = 2.7568153900; my $c2 = 1.3067284816; my $c3 = 1.7023821103*(10**(-1)); my $d1 = 7.3700164250*(10**(-1)); my $d2 = 1.2021132975*(10**(-1)); # HASH SUM CD 15.7614929821 # Coefficients for P near 0 or 1. my $e0 = 6.6579051150; my $e1 = 3.0812263860; my $e2 = 4.2868294337*(10**(-1)); my $e3 = 1.7337203997*(10**(-2)); my $f1 = 2.4197894225*(10**(-1)); my $f2 = 1.2258202635*(10**(-2)); # HASH SUM EF 19.4052910204 $ifault = 0; $q = $p - $half; if(abs($q) <= $split1) { $r = $const1 - $q * $q; $normal_dev = $q * ((($a3 * $r + $a2) * $r + $a1) * $r + $a0) / ((($b3 * $r + $b2) * $r + $b1) * $r + $one); } else{ if($q < $zero) { $r = $p;} else { $r = $one - $p; } if($r <= $zero) { $ifault = 1; $normal_dev = $zero; return ($normal_dev, $ifault); } $r = (-log($r))**0.5; if($r <= $split2) { $r = $r - $const2; $normal_dev = ((($c3 * $r + $c2) * $r + $c1) * $r + $c0) / (($d2 * $r + $d1) * $r + $one); } else{ $r = $r - $split2; $normal_dev = ((($e3 * $r + $e2) * $r + $e1) * $r + $e0) / (($f2 * $r + $f1) * $r + $one); } if($q < $zero) {$normal_dev = - $normal_dev;} return ($normal_dev, $ifault); } } ################################ alnorm function ##################################################################### #FUNCTION alnorm(x, upper) RESULT(fn_val) # Evaluates the tail area of the standardised normal curve from x to infinity if upper is .true. or # from minus infinity to x if upper is .false. sub alnorm { # get the inputs my ($x, $upper) = @_; # define the output my $fn_val; my $zero = 0.0; my $one = 1.0; my $half = 0.5; my $con = 1.28; my $z; my $y; my $up; #!*** machine dependent constants my $ltone = 7.0; my $utzero = 18.66; my $p = 0.398942280444; my $q = 0.39990348504; my $r = 0.398942280385; my $a1 = 5.75885480458; my $a2 = 2.62433121679; my $a3 = 5.92885724438; my $b1 = -29.8213557807; my $b2 = 48.6959930692; my $c1 = -3.8052*(10**(-8)); my $c2 = 3.98064794*(10**(-4)); my $c3 = -0.151679116635; my $c4 = 4.8385912808; my $c5 = 0.742380924027; my $c6 = 3.99019417011; my $d1 = 1.00000615302; my $d2 = 1.98615381364; my $d3 = 5.29330324926; my $d4 = -15.1508972451; my $d5 = 30.789933034; $up = $upper; $z = $x; if($z < $zero){ if($up == 0){$up = 1;} else {$up = 0;} $z = -$z; } if($z <= $ltone || $up && $z <= $utzero){ $y = $half*$z*$z; if($z > $con) {$fn_val = $r*exp(-$y)/($z+$c1+$d1/($z+$c2+$d2/($z+$c3+$d3/($z+$c4+$d4/($z+$c5+$d5/($z+$c6))))));} else {$fn_val = $half - $z*($p - $q*$y/($y+$a1+$b1/($y+$a2+$b2/($y+$a3))));} } else{ $fn_val = $zero; } if(!$up) {$fn_val = $one - $fn_val}; return $fn_val; } ##################################### poly function ######################################################### # FUNCTION poly(c, nord, x) RESULT(fn_val) # Calculates the algebraic polynomial of order nored-1 with array of coefficients c. Zero order coefficient is c(1) sub poly_ { my ($c, $nord, $x) = @_; my $fn_val; my $i; my $j; my $n2; my $p; $fn_val = @$c[1-1]; if($nord == 1) {return $fn_val;} $p = $x*@$c[$nord-1]; if($nord == 2) { $fn_val = $fn_val + $p; } else { $n2 = $nord - 2; $j = $n2 + 1; for($i = 1; $i <= $n2; $i++){ $p = ($p + @$c[$j-1])*$x; $j = $j - 1; } $fn_val = $fn_val + $p; } return $fn_val; } ###################################### min function ############################################ # FUNCTION min(a,b) RESULT min of a, b sub min { my ($a, $b) = @_; if($a <= $b) { return $a; } else { return $b; } } ###################################### sign function ############################################ # FUNCTION sign(a,b) RESULT sign of a, b sub sign { my ($a) = @_; if($a >= 0) { return 1; } else { return -1; } } ###################################### asin function ############################################ # FUNCTION asin(a) RESULT arcsin of a sub asin { my ($a) = @_; if($a > 1 || $a < -1) { print "error: abs sin value > 1"; return 0; } else { my $b = (1-$a**2)**0.5; my $fn_val = atan2($a, (1-$a**2)**0.5); my $fn_test = (1-$a**2)**0.5; return $fn_val; } }