Collection of scripts
From Bioinformatikpedia
A completely unordered, yet to become truly useful collection of scripts we used.
Contents
Sequence Alignments
PSIBlasttrainer.pl
<source lang="perl">
#! /usr/bin/perl
use strict;
use Getopt::Long;
my $input;
my $output;
my $database;
my $maxIt;
my $before;
my $after;
my $result = GetOptions ("i=s" => \$input,"o=s" => \$output,"d=s" => \$database,"j=i" => \$maxIt);
open(TIME ,">","time.txt");
print TIME "\# time used for psiblast\n";
#run psiblast each time and save the time;
for(my $i =1;$i<=$maxIt;$i++){
print "iteration: $i\n";
$before = time();
open STATUS, "-|","time blastpgp -j $i -d $database -i $input -o $output"."_".$i."_it"
or die "can't fork: $!";
while(<STATUS>){
print TIME $_;
}
$after = time();
print TIME ($after-$before)."\n";
close STATUS;
}
print TIME ">";
for(my $i=1;$i<$maxIt;$i++){
my $eval = 1/(10**$i);
print "iteration: $i\n";
$before = time();
system("time blastpgp -j 1 -d $database -i $input -o $output" . "_eVal_" . "$eval -e $eval");
$after = time();
print TIME ($after-$before)."\n";
close STATUS;
}
print TIME ">\n"
for(my $i=1;$i<$maxIt;$i++){
my $eval = 1/(10**$i);
print "iteration: $i\n";
$before = time();
system("time blastpgp -j 1 -d $database -i $input -o $output" . "_integr_" . "$eval -h $eval");
$after = time();
print TIME ($after-$before)."\n";
close STATUS;
}
close TIME;
</source>
Sequence Alignment Statistics
<source lang="python">
#!/usr/bin/env python
#simple sript to count gaps and conserved columns in multiple alignment files
import sys
from collections import defaultdict
def default_string():
return ""
def aln_stats(filename):
fh = open(filename,'r')
sequences = defaultdict(default_string)
for line in fh:
if line[:2].strip() and not line.startswith("CLUSTAL"):
seq = line.split()
sequences[seq[0]]+="".join(seq[1:])
fh.close()
for key in sequences:
print key, sequences[key].count('-')
print "conserved:",conserved(sequences)
def fasta_stats(filename):
fh = open(filename,'r')
gap_count = 0
seq_id = ""
sequences = defaultdict(default_string)
for line in fh:
if line.startswith(">"):
if gap_count:
print seq_id, gap_count
gap_count = 0
seq_id = line.split()[0][1:]
else:
gap_count+=line.count('-')
sequences[seq_id]+=line.strip()
print seq_id, gap_count,"\nconserved:",conserved(sequences)
fh.close()
def conserved(sequence_dict):
conserved_count = 0
for i in range(len(sequence_dict.values()[0])):
col = set([])
for seq in sequence_dict.values():
col.add(seq[i])
if len(col)== 1:
conserved_count+=1
return conserved_count
if "--help" in sys.argv or len(sys.argv)<2:
print "usage: python %s <filename>"%sys.argv[0]
elif sys.argv[1].endswith(".aln"):
aln_stats(sys.argv[1])
elif sys.argv[1].endswith(".fasta"):
fasta_stats(sys.argv[1])
else:
print "Only .aln or .fasta files, sorry!"
</source>
HHextract.py
#!/usr/bin/env python
#this simply takes output of HHblits, extracts the IDs of cluster members and adds a clusteridentifier
#output:
#ID1 CL1 E-Value Identities
#ID2 CL1 E-Value Identities
#ID3 CL1 E-Value Identities
#ID4 CL2 E-Value Identities
#ID4 CL2 E-Value Identities
#..
#
#usage: python hhextract.py <infile> <outfile>
import sys, re
try:
infile = open(sys.argv[1])
except IOError:
print "Couldn't open input file"
exit(-1)
try:
outfile= open(sys.argv[2],'w')
except Exception:
print "Couldn't open output file"
exit(-1)
for line in infile:
if line.startswith('>'):
splits = line.split('|')
to_find = int(splits[2])
#check number of clustermembers, skip and print clusterID if confusion
#if len(splits)!= (4+to_find):
# print line[:15]
# print to_find, splits
# exit(-1)
line = infile.next()
splits2 = line.split()
for member in splits[-to_find:]:
memberID = member.split()[0].strip()
if memberID.endswith('.'):
memberID = memberID[:-1]
outfile.write("%s %s %s %s\n"%(memberID, splits[1], splits2[1].split('=')[1], splits2[4].split('=')[1]))
infile.close()
outfile.close()
getEvalues.pl
#!/usr/bin/perl
use strict;
use DirHandle;
my $dir = $ARGV[0];
my $blast = $ARGV[1];
sub plainfiles {
my $dir = shift;
my $dh = DirHandle->new($dir) or die "can't opendir $dir: $!";
return sort # sort pathnames
grep { -f } # choose only "plain" files
map { "$dir/$_" } # create full paths
grep { !/^\./ } # filter out dot files
grep { !/\.dat$/}
grep { !/\.pl$/}
grep { !/\.py$/}
grep { !/\.png$/}
$dh->
read()
; # read all entries
}
my @files = plainfiles($dir);
if($blast eq "blast"){
for(@files){
open(READER ,"<",$_);
open(WRITER ,">",$_.".dat");
my $eval;
while(<READER>){
if(/Expect = (.*?),/){
#print "buuuuu";
if($1 == 0){
$eval = "-INF";
}else{
$eval = log($1)/log(10);
}
#Identities = 314/440 (71%)
}elsif(/Identities = .*?\/.*? \((.*?)\%\),/){
#print "tralaöa";
print WRITER "$eval 0\.$1\n";
}elsif(/Results of round/){
close WRITER;
open(WRITER ,">",$_.".dat");
}
}
close READER;
close WRITER;
}
}else{
for(@files){
open(READER ,"<",$_);
open(WRITER ,">",$_.".dat");
while(<READER>){
my @fields = split(" ",$_);
my $eval;
if($fields[2] == 0){
$eval = "-INF";
}else{
$eval = log($fields[2])/log(10);
}
my $ident =$fields[3];
$ident =~ s/\%//;
$ident = "0."+$ident;
print WRITER "$eval $ident\n";
}
close READER;
close WRITER;
}
}
Sequence based predictions
ss_score.py
#!/usr/bin/env python
#calculates Q3 and SOV for two (already aligned) assignments of structure
#in files containing only the structure (no comment line, no header, mayyybe newlines..)
#usage: python ss_score.py <dssp_file> <prediction_file>
import sys
def main():
#read files, map DSSP characters to EHL and C to L
#strip of newlines..
dssp = open(sys.argv[1]).read().strip().replace("S","L").replace("B","L").replace("I","L").replace("G","H").replace("T","L").replace("\n","")
pred_tmp = open(sys.argv[2]).read().strip().replace("C","L").replace("\n","")
#if DSSP has only '-', ignore in prediction as well
pred = ""
for i in range(len(dssp)):
if dssp[i] == "-":
pred+= "-"
else:
pred+=pred_tmp[i]
q_values = q3(dssp,pred)
sov_values = sov(dssp,pred)
print "Q3 =", q_values[0],"\nQ_E =", q_values[1],"\nQ_H =", q_values[2],"\nQ_L =", q_values[3]
print "SOV =", sov_values[0],"\nSOV_E =", sov_values[1],"\nSOV_H =", sov_values[2],"\nSOV_L =", sov_values[3]
def q3(dssp,pred):
residues_E = 0
residues_H = 0
residues_L = 0
match_E = 0
match_H = 0
match_L = 0
residues = {'E':residues_E,'H':residues_H,'L':residues_L}
match = {'E':match_E,'H':match_H,'L':match_L}
for i in range(len(dssp)):
if dssp[i] != "-":
residues[dssp[i]]+=1
if dssp[i] == pred[i]:
match[dssp[i]]+=1
matches = sum(match.values())
resid = sum(residues.values())
return (matches*100.0/resid,match['E']*100.0/residues['E'],match['H']*100.0/residues['H'],match['L']*100.0/residues['L'])
def sov(dssp,pred):
sov = 0
sov_E = 0
sov_H = 0
sov_L = 0
segment_sum = 0
for typ in ["E","H","L"]:
stretch_A = []
stretch_B = []
started = False
start = 0
sov_x = 0
segment_x = 0
for pairs in [(stretch_A, dssp),(stretch_B, pred)]:
seq = pairs[1]
sets = pairs[0]
for i in range(len(seq)):
if not started and seq[i] == typ:
started = True
start = i
if started and seq[i] != typ:
started = False
#first position and first position after
sets.append((start,i))
start = 0
for segment in stretch_A:
segment_x+=segment[1]-segment[0]
overlapping_pairs = []
a = 0
b = 0
while a < len(stretch_A) and b < len(stretch_B):
a_start = stretch_A[a][0]
a_end = stretch_A[a][1]
b_start = stretch_B[b][0]
b_end = stretch_B[b][1]
if a_start <= b_start:
if b_start <= a_end:
overlapping_pairs.append((stretch_A[a],stretch_B[b]))
b+=1
else:
a+=1
else:
if a_start <= b_end:
overlapping_pairs.append((stretch_A[a],stretch_B[b]))
a+=1
else:
b+=1
segment_sum+=segment_x
for pair in overlapping_pairs:
sov_x+= (pair[0][1]-pair[0][0])*(minov(pair)+delta(pair))/maxov(pair)
sov+=sov_x
if typ == 'E':
sov_E = sov_x*100/segment_x
elif typ == 'H':
sov_H = sov_x*100/segment_x
elif typ =='L':
sov_L = sov_x*100/segment_x
return (sov*100/segment_sum,sov_E,sov_H, sov_L)
def minov(pair):
a = pair[0]
b = pair[1]
return float(min(a[1],b[1]) - max(a[0],b[0]))
def maxov(pair):
a = pair[0]
b = pair[1]
return float(max([a[1],b[1]]) - min([a[0],b[0]]))
def delta(pair):
return float(min([maxov(pair)-minov(pair),minov(pair),(pair[0][1]-pair[0][0])/2,(pair[1][1]-pair[1][0])/2]))
main()
