1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
|
#!/usr/bin/env perl
use strict;
use warnings;
use Carp;
use Getopt::Long qw(:config no_ignore_case bundling pass_through);
use File::Basename;
my $usage = <<__EOUSAGE__;
###################################################################################
#
# --target <string> 'genes' or 'samples'
#
# -K <int> define K clusters via k-means algorithm
#
# or, cut the hierarchical tree:
#
# --Ktree <int> cut tree into K clusters
#
# --Ptree <float> cut tree based on this percent of max(height) of tree
#
# -R <string> the filename for the store RData (file.all.RData)
#
###################################################################################
__EOUSAGE__
;
my $Kmeans;
my $Ktree;
my $help_flag = 0;
my $R_data_file;
my $pct_height = 0;
my $target = undef;
my $lexically_order_columns;
my $no_column_reordering;
&GetOptions ( 'h' => \$help_flag,
'target=s' => \$target,
'K=i' => \$Kmeans,
'Ktree=i' => \$Ktree,
'Ptree=f' => \$pct_height,
'R=s' => \$R_data_file,
'lexical_column_ordering' => \$lexically_order_columns,
'no_column_reordering' => \$no_column_reordering,
);
if ($help_flag) {
die $usage;
}
if (@ARGV) {
die "Error, don't understand args: @ARGV";
}
unless ($target && $target =~ /^(genes|samples)$/ && ($Kmeans || $Ktree || $pct_height) && $R_data_file) {
die $usage;
}
if ($pct_height && $pct_height < 1) {
die "Error, specify --Ptree as percent value > 1\n\n";
}
main: {
unless (-s $R_data_file) {
die "Error, cannot find pre-existing R-session data as file: $R_data_file";
}
my $R_script = "__tmp_define_clusters.R";
open (my $ofh, ">$R_script") or die "Error, cannot write to file $R_script";
print $ofh "library(cluster)\n";
#print $ofh "library(gplots)\n";
print $ofh "library(Biobase)\n";
print $ofh "library(fastcluster)\n";
print $ofh "source(\"/usr/lib/trinityrnaseq/Analysis/DifferentialExpression/R/heatmap.3.R\")\n";
print $ofh "load(\"$R_data_file\")\n";
my $core_filename;
my $outdir;
if ($target eq 'samples') {
print $ofh "hc_features = hc_samples\n";
}
else {
print $ofh "hc_features = hc_genes\n";
}
if ($Kmeans) {
print $ofh "kmeans_clustering <- kmeans(data, centers=$Kmeans, iter.max=100, nstart=5)\n";
$core_filename = "clusters_fixed_Kmeans_${Kmeans}";
print $ofh "partition_assignments = kmeans_clustering\$cluster\n";
}
elsif ($Ktree) {
print $ofh "partition_assignments <- cutree(as.hclust(hc_features), k=$Ktree)\n";
$core_filename = "clusters_fixed_Ktree_${Ktree}";
}
else {
print $ofh "partition_assignments <- cutree(as.hclust(hc_features), h=$pct_height/100*max(hc_features\$height))\n";
$core_filename = "clusters_fixed_P_${pct_height}";
}
print $ofh "partition_assignments = as.data.frame(partition_assignments)\n";
print $ofh "cluster_names = paste('cl_', partition_assignments[,1], sep='')\n";
print $ofh "partition_assignments = cbind(cluster_names, rownames(partition_assignments))\n";
print $ofh "write.table(partition_assignments[order(cluster_names),], col.names=F, row.names=F, file=\'$core_filename.${target}_clusters\', quote=F, sep='\t')\n";
close $ofh;
&process_cmd("R --no-save --no-restore --no-site-file --no-init-file -q < $R_script");
exit(0);
}
####
sub process_cmd {
my ($cmd) = @_;
print STDERR "CMD: $cmd\n";
my $ret = system($cmd);
if ($ret) {
die "Error, cmd $cmd died with ret $ret";
}
return;
}
|
