Mercurial > repos > yusuf > combine_hgvs_annotations
comparison combine_hgvs_tables @ 0:baf1543e8ae1 default tip
initial commit
author | Yusuf Ali <ali@yusuf.email> |
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date | Wed, 25 Mar 2015 13:27:49 -0600 |
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-1:000000000000 | 0:baf1543e8ae1 |
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1 #!/usr/bin/env perl | |
2 | |
3 use strict; | |
4 use warnings; | |
5 | |
6 if(@ARGV == 1 and $ARGV[0] eq "-v"){ | |
7 print "Version 1.0\n"; | |
8 exit; | |
9 } | |
10 | |
11 my $quiet = 0; | |
12 if(@ARGV and $ARGV[0] =~ /^-q(?:uiet)?$/){ | |
13 $quiet = 1; | |
14 shift @ARGV; | |
15 } | |
16 | |
17 @ARGV >= 6 and not @ARGV%2 or die "Usage: $0 [-q(uiet)] <true|false> <output file> <method_name1> <hgvs_file_1.txt> <method_name2> <hgvs_file_2.txt> ...\n", | |
18 "Where true or false determines if the genotypes calls should all be reported (if false, they are collapsed to the unique set of values observed)\n"; | |
19 | |
20 my %zygosity; | |
21 my %quality; | |
22 my %var_count; | |
23 my %tot_count; | |
24 my %methods; | |
25 my %data; | |
26 my $chr_prefix_exists = 0; # do any of the tools report chr1, if so we need to ensure 1 get reported as chr1 later for consistency across tools | |
27 | |
28 my $collapse = $ARGV[0] =~ /^true$/i; | |
29 | |
30 open(OUT, ">$ARGV[1]") | |
31 or die "Cannot open $ARGV[1] for writing: $!\n"; | |
32 | |
33 my @headers; | |
34 my ($chr_column, $zygosity_column, $pvalue_column, $alt_cnt_column, $tot_cnt_column, $transcript_column, $cdna_hgvs_column, $pos_column, $to_column, $srcs_column); | |
35 for(my $i=2; $i<$#ARGV; $i+=2){ | |
36 my $method_name = $ARGV[$i]; | |
37 my $infile = $ARGV[$i+1]; | |
38 print STDERR "Processing $infile...\n" unless $quiet; | |
39 open(IN, $infile) | |
40 or die "Cannot open $infile for reading: $!\n"; | |
41 my $header = <IN>; # header | |
42 chomp $header; | |
43 if($i == 2){ | |
44 @headers = split /\t/, $header; | |
45 for(my $j = 0; $j <= $#headers; $j++){ | |
46 if($headers[$j] eq "Chr"){ | |
47 $chr_column = $j; | |
48 } | |
49 elsif($headers[$j] eq "Zygosity"){ | |
50 $zygosity_column = $j; | |
51 } | |
52 elsif($headers[$j] eq "P-value"){ | |
53 $pvalue_column = $j; | |
54 } | |
55 elsif($headers[$j] eq "Variant Reads"){ | |
56 $alt_cnt_column = $j; | |
57 } | |
58 elsif($headers[$j] eq "Total Reads"){ | |
59 $tot_cnt_column = $j; | |
60 } | |
61 elsif($headers[$j] eq "Selected transcript"){ | |
62 $transcript_column = $j; | |
63 } | |
64 elsif($headers[$j] eq "Transcript HGVS"){ | |
65 $cdna_hgvs_column = $j; | |
66 } | |
67 elsif($headers[$j] eq "DNA From"){ | |
68 $pos_column = $j; | |
69 } | |
70 elsif($headers[$j] eq "DNA To"){ | |
71 $to_column = $j; | |
72 } | |
73 elsif($headers[$j] eq "Sources"){ | |
74 $srcs_column = $j; | |
75 } | |
76 } | |
77 if(defined $srcs_column){ | |
78 # print header as-is | |
79 print OUT "$header\n"; | |
80 } | |
81 else{ | |
82 # print header from the first file, with extra column for methods at the end | |
83 push @headers, "Sources"; | |
84 $srcs_column = $#headers; | |
85 print OUT join("\t", @headers), "\n"; | |
86 } | |
87 } | |
88 else{ | |
89 # Make sure the columns are the same in the various files | |
90 my @latest_headers = split /\t/, $header; | |
91 for(my $j = 0; $j <= $#latest_headers && $j <= $#headers; $j++){ | |
92 if($latest_headers[$j] ne $headers[$j]){ | |
93 die "Header column ", $j+1, "($latest_headers[$j]) in $ARGV[$i] is different from the equivalent column label ($headers[$j]) in $ARGV[2]. Aborting, cannot merge the files.\n"; | |
94 } | |
95 } | |
96 } | |
97 while(<IN>){ | |
98 chomp; | |
99 my @F = split /\t/, $_, -1; # -1 to keep trailing blank fields | |
100 if(not $chr_prefix_exists and $F[$chr_column] =~ /^chr/){ | |
101 $chr_prefix_exists = 1; | |
102 } | |
103 $F[$chr_column] =~ s/^chr//; # for consistency | |
104 my $key = "$F[$transcript_column]:$F[$cdna_hgvs_column]"; # transcript_id:cdna_hgvs is shared id for common variants amongst files | |
105 # record disagreement on zygosity if any | |
106 if(not defined $zygosity{$key}){ | |
107 $zygosity{$key} = []; | |
108 $quality{$key} = []; | |
109 $var_count{$key} = []; | |
110 $tot_count{$key} = []; | |
111 $data{$key} = \@F; | |
112 #print STDERR "Missing fields (only have ", scalar(@F), " for input '$_'\n" if $#F < $#headers; | |
113 } | |
114 push @{$zygosity{$key}}, split(/; /,$F[$zygosity_column]); | |
115 push @{$quality{$key}}, $F[$pvalue_column]; | |
116 push @{$var_count{$key}}, $F[$alt_cnt_column]; | |
117 push @{$tot_count{$key}}, $F[$tot_cnt_column]; | |
118 push @{$methods{$key}}, $method_name; | |
119 } | |
120 close(IN); | |
121 } | |
122 | |
123 if($chr_prefix_exists){ | |
124 for my $key (keys %data){ | |
125 # assuming there is a mix of chr1 and 1, always add the chr for consistency | |
126 $data{$key}->[$chr_column] = "chr".$data{$key}->[$chr_column] unless $data{$key}->[$chr_column] =~ /^chr/; | |
127 } | |
128 } | |
129 | |
130 # Sort by chr, then pos, then transcript_id | |
131 for my $key (sort {$data{$a}->[$chr_column] cmp $data{$b}->[$chr_column] or | |
132 $data{$a}->[$pos_column] <=> $data{$b}->[$pos_column] or | |
133 $data{$a}->[$to_column] <=> $data{$b}->[$to_column] or | |
134 $data{$a}->[$transcript_column] cmp $data{$b}->[$transcript_column]} keys %data){ | |
135 # Before printing a line, merge the zygosity, variant quality, read count data if requested | |
136 my %seen; | |
137 if($collapse){ | |
138 my @zygosities = grep {$_ ne "NA" and not $seen{$_}++} @{$zygosity{$key}}; | |
139 if(@zygosities == 0){ | |
140 # do nothing, existing NA in 7th column will be a fine answer as they are all like tha | |
141 } | |
142 elsif(@zygosities == 1){ | |
143 # agreement by all methods, just print the one not NA | |
144 $data{$key}->[$zygosity_column] = $zygosities[0] if $data{$key}->[$zygosity_column] eq "NA"; | |
145 } | |
146 else{ | |
147 $data{$key}->[$zygosity_column] = join("/", sort keys %seen); # list all unique values that occur | |
148 } | |
149 } | |
150 else{ | |
151 $data{$key}->[$zygosity_column] = join("; ", @{$zygosity{$key}}); | |
152 } | |
153 | |
154 if($collapse){ | |
155 undef %seen; | |
156 my @qualities = grep {$_ ne "NA" and not $seen{$_}++} @{$quality{$key}}; | |
157 if(@qualities == 0){ | |
158 # do nothing, existing NA in 8th column will be a fine answer as they are all like that | |
159 } | |
160 elsif(@qualities == 1){ | |
161 # agreement by all methods, just print the one not NA | |
162 $data{$key}->[$pvalue_column] = $qualities[0] if $data{$key}->[8] eq "NA"; | |
163 } | |
164 else{ | |
165 # calculate the median for the collapsed value | |
166 my @sorted_qualities = sort {$a <=> $b} grep({$_ ne "NA"} @{$quality{$key}}); | |
167 my $median_quality = $sorted_qualities[int($#sorted_qualities/2)]; # rounds down (actually better score as this is a p-value) | |
168 $data{$key}->[$pvalue_column] = $median_quality; | |
169 } | |
170 } | |
171 else{ | |
172 $data{$key}->[$pvalue_column] = join("; ", @{$quality{$key}}); | |
173 } | |
174 | |
175 if($collapse){ | |
176 undef %seen; | |
177 my @var_counts = grep {$_ ne "NA" and not $seen{$_}++} @{$var_count{$key}}; | |
178 undef %seen; | |
179 my @tot_counts = grep {$_ ne "NA" and not $seen{$_}++} @{$tot_count{$key}}; | |
180 if(@var_counts == 0 and @tot_counts == 0){ | |
181 # do nothing, existing NAs okay | |
182 } | |
183 elsif(@var_counts == 1 and @tot_counts == 1){ | |
184 # agreement by all methods, just print the one in %data unless it's NA | |
185 $data{$key}->[$alt_cnt_column] = $var_counts[0] if $data{$key}->[$alt_cnt_column] eq "NA"; | |
186 $data{$key}->[$tot_cnt_column] = $tot_counts[0] if $data{$key}->[$tot_cnt_column] eq "NA"; | |
187 } | |
188 else{ | |
189 # calculate the median for the collapsed value | |
190 my @sorted_var_counts = sort {$a <=> $b} grep({$_ ne "NA"} @{$var_count{$key}}); | |
191 my $pivot = $#sorted_var_counts/2; | |
192 my $median_var_count = $pivot == int($pivot) ? $sorted_var_counts[$pivot] : # arithmetic mean | |
193 int(($sorted_var_counts[int($pivot)]+$sorted_var_counts[int($pivot)+1])/2); | |
194 $data{$key}->[$alt_cnt_column] = $median_var_count; | |
195 my @sorted_tot_counts = sort {$a <=> $b} grep({$_ ne "NA"} @{$tot_count{$key}}); | |
196 $pivot = $#sorted_tot_counts/2; | |
197 my $median_tot_count = $pivot == int($pivot) ? $sorted_tot_counts[$pivot] : # arithmetic mean | |
198 int(($sorted_tot_counts[int($pivot)]+$sorted_tot_counts[int($pivot)+1])/2); | |
199 $data{$key}->[$tot_cnt_column] = $median_tot_count; | |
200 } | |
201 } | |
202 else{ | |
203 # list the raw numbers | |
204 $data{$key}->[$alt_cnt_column] = join("; ", @{$var_count{$key}}); | |
205 $data{$key}->[$tot_cnt_column] = join("; ", @{$tot_count{$key}}); | |
206 } | |
207 | |
208 # to facilitate multiple rounds of combining, slash the extra column from the last round if it exists | |
209 $data{$key}->[$srcs_column] = join("; ", @{$methods{$key}}); | |
210 for(my $i = 0; $i <= $#{$data{$key}}; $i++){ | |
211 $data{$key}->[$i] = "" if not defined $data{$key}->[$i]; | |
212 } | |
213 print OUT join("\t", @{$data{$key}}), "\n"; | |
214 } | |
215 close(OUT); |