Sequence Alignments Protocol TSD
From Bioinformatikpedia
The results are shown in Sequence Alignments TSD.
Contents
Blast
<source lang="bash">
blastall -p blastp -d /mnt/project/pracstrucfunc12/data/big/big_80 -i /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/P06865.fasta -b 1200 -v 1200 > /mnt/home/student/meiera /1_SeqAli/1_SeqSearch/blastall_1200alis.out
</source>
PSI-Blast
Big80
<source lang="bash"> time blastpgp -C blastpgp1200_pssmdefault -d /mnt/project/pracstrucfunc12/data/big/big_80 -i /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/P06865.fasta -v 1200 -b 1200 > /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/blastpgp1200_default.out time blastpgp -C blastpgp1200_pssmit2e002 -d /mnt/project/pracstrucfunc12/data/big/big_80 -i /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/P06865.fasta -j 2 -h "0.002" -v 1200 -b 1200 > /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/blastpgp1200_it2e002.out time blastpgp -C blastpgp1200_pssmit10e002 -d /mnt/project/pracstrucfunc12/data/big/big_80 -i /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/P06865.fasta -j 10 -h "0.002" -v 1200 -b 1200 > /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/blastpgp1200_it10e002.out time blastpgp -C blastpgp1200_pssmit10e-10 -d /mnt/project/pracstrucfunc12/data/big/big_80 -i /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/P06865.fasta -j 10 -h "10E-10" -v 1200 -b 1200 > /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/blastpgp1200_it10e-10.out time blastpgp -C blastpgp1200_pssmit2e-10 -d /mnt/project/pracstrucfunc12/data/big/big_80 -i /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/P06865.fasta -j 2 -h "10E-10" -v 1200 -b 1200 > /mnt/home/student/meiera/1_SeqAli/1_SeqSearch/blastpgp1200_it2e-10.out </source>
Big
<source lang="bash">
PAT="/mnt/home/student/meiera/1_SeqAli/1_SeqSearch" time blastpgp -R $PAT/blastpgp1200_pssmit2e002 -d /mnt/project/pracstrucfunc12/data/big/big -i $PAT/P06865.fasta -v 3800 -b 3800 > $PAT/blastpgpBIG_3800_it2e002.out time blastpgp -R $PAT/blastpgp1200_pssmit10e002 -d /mnt/project/pracstrucfunc12/data/big/big -i $PAT/P06865.fasta -v 3800 -b 3800 > $PAT/blastpgpBIG_3800_it10e002.out time blastpgp -R $PAT/blastpgp1200_pssmit2e-10 -d /mnt/project/pracstrucfunc12/data/big/big -i $PAT/P06865.fasta -v 3800 -b 3800 > $PAT/blastpgpBIG_3800_it2e-10.out time blastpgp -R $PAT/blastpgp1200_pssmit10e-10 -d /mnt/project/pracstrucfunc12/data/big/big -i $PAT/P06865.fasta -v 3800 -b 3800 > $PAT/blastpgpBIG_3800_it10e-10.out
</source>
Count unique matches: example
<source lang="bash">
head -1 m8blastpgp1200_it2e002.out grep -n G1RUL9 m8blastpgp1200_it2e002.out tail -n +1233 m8blastpgp1200_it2e002.out | cut -f 2 | wc -l tail -n +1233 m8blastpgp1200_it2e002.out | uniq -w 44 | wc -l
</source>
HHblits
<source lang="bash">
WD="/mnt/home/student/meiera/1_SeqAli/1_SeqSearch" time hhblits -i $WD/P06865.fasta -o $WD/hhblits_460_P06865.hhr -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -Z 460 -B 460 > $WD/hhblits_460_P06865_stdout.log time hhblits -i $WD/P06865.fasta -n 10 -o $WD/hhblits_460_P06865_10it.hhr -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -Z 460 -B 460 > $WD/hhblits_460_P06865_10_stdout.log time hhblits -i $WD/P06865.fasta -n 10 -o $WD/hhblits_2500_P06865_10it.hhr -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -Z 2500 -B 2500 > $WD/hhblits_2500_P06865_10_stdout.log time hhblits -i $WD/P06865.fasta -n 2 -o $WD/hhblits_460_P06865_2it.hhr -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -Z 460 -B 460 > $WD/hhblits_460_P06865_2_stdout.log time hhblits -i $WD/P06865.fasta -n 2 -o $WD/hhblits_2500_P06865_2it.hhr -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -Z 2500 -B 2500 > $WD/hhblits_2500_P06865_2_stdout.log time hhsearch -i $WD/P06865.fasta -o $WD/hhblits_460_P06865.hhr -d /mnt/project/pracstrucfunc12/data/hhblits/pdb70_current_hhm_db -Z 14 -B 14 > $WD/hhblits_pdb_1500_P06865_stdout.log
</source>
Preparation of outputs
Sequence identity and e-values
<source lang="bash">
#for both Blast and HHblits output /mnt/home/student/meiera/bin/1_parseidentity.pl Usage: 1_parseidentity.pl [flags] file... flags: -i Infile reads the input from fileIN -o OutFile writes output to fileOUT -h Input is hhblits, default is blast
</source>
Uniprot sets for Venn diagrams
<source lang="bash">
#for both Blast and HHblits output, also computation of the unique ids for HHblits /mnt/home/student/meiera/bin/1_getUniprotIDS.pl Usage: 1_getUniprotIDS.pl [flags] file... flags: -i Infile reads the input from fileIN -o OutFile writes uniprot identifiers to fileOUT -h = hhblits input default is set to blastoutput -m mappingfile uniprot mappingfile
</source>
Build PDB sets
Unique identifiers for Blast and HHblits
<source lang="bash">
/mnt/home/student/meiera/bin/1_forPdbMapping.pl Usage: 1_forPdbMapping.pl [flags] file... flags: -i Infile reads the input from fileIN -o OutFile writes uniprot identifiers to fileOUT -h = hhblits input, default is set to blastoutput
#Use uniprot.org's online mapping service on the .pdbmapping files and save the results to .mapped files
cut -f 2 psiblastBIGit10e002.mapped | tr '[A-Z]' '[a-z]' | sort | uniq | grep -P "\w{4}" > psiblastBIGit10e002.finpdb1
grep -P "\w{4}_" psiblastBIGit10e002.pdbmapping --only-matching | sed "s/_//" > psiblastBIGit10e002.finpdb2
cat psiblastBIGit10e002.finpdb2 psiblastBIGit10e002.finpdb1 | sort | uniq > psiblastBIGit10e002.finpdb
cut -f 2 psiblastBIGit10e-10.mapped | tr '[A-Z]' '[a-z]' | sort | uniq | grep -P "\w{4}" > psiblastBIGit10e-10.finpdb1
grep -P "\w{4}_" psiblastBIGit10e-10.pdbmapping --only-matching | sed "s/_//" > psiblastBIGit10e-10.finpdb2
cat psiblastBIGit10e-10.finpdb1 psiblastBIGit10e-10.finpdb2 | sort | uniq > psiblastBIGit10e-10.finpdb
cut -f 2 psiblastBIGit2e002.mapped | tr '[A-Z]' '[a-z]' | sort | uniq | grep -P "\w{4}" > psiblastBIGit2e002.finpdb1
grep -P "\w{4}_" psiblastBIGit2e002.pdbmapping --only-matching | sed "s/_//" > psiblastBIGit2e002.finpdb2
cat psiblastBIGit2e002.finpdb1 psiblastBIGit2e002.finpdb2 | sort | uniq > psiblastBIGit2e002.finpdb
cut -f 2 psiblastBIGit2e-10.mapped | tr '[A-Z]' '[a-z]' | sort | uniq | grep -P "\w{4}" > psiblastBIGit2e-10.finpdb1
grep -P "\w{4}_" psiblastBIGit2e-10.pdbmapping --only-matching | sed "s/_//" > psiblastBIGit2e-10.finpdb2
cat psiblastBIGit2e-10.finpdb1 psiblastBIGit2e-10.finpdb2 | sort | uniq > psiblastBIGit2e-10.finpdb
cut -f 2 hhblits__460.mapped | tr '[A-Z]' '[a-z]' | sort | uniq | grep -P "\w{4}" > hhbtemp
sed "s/_\w//g" hhblits_pdb_1500.pdbmapping > hhbtemp2
cat hhbtemp hhbtemp2 | sed "s/\s//g" | sort | uniq > hhblits.finpdb
rm -f hhbtemp hhbtemp2
# dont' have to do the special stuff here, the normal one doesn't find any because it's only on uniprot
</source>
COPS Parsing
The following script will read the COPS clusters (-c) and print out for every classification the members of the cluster that one or several IDs of interest (-i) are contained in. Additionally, if given a list of hits (-hi), it will count the number of hits that fall in the according cluster and the ones that don't and print out that information to a file for plotting e.g. with R. Note that you can ignore chains with the '-nc' option.
Also be aware that ignoring chains might lead to a merge of clusters. That is if given xxxx als protein of interest and xxxx,A as well was xxxx,B are contained in COPS, the final cluster which is used to calculate how many hits fall into it, will be a combination of the cluster from xxxx,A and the one from xxxx,B. That of course might be overestimating the number of hits that fall into a cluster.
Sample call: ./parseCOPSClusters.pl -c ~/Desktop/COPS-ChainHierarchy.txt -i ./interestIds -nc -hi ./union.finpdb
<source lang="perl">
#!/usr/bin/env perl
use strict;
use warnings;
use sigtrap;
use autodie;
use diagnostics;
use Pod::Usage;
use Getopt::Long qw(:config require_order);
use 5.010; #For smart match, which makes this script unbelievably slow, but I'm lazy :)
##Program variables
my %clusters;
my @clusterOrder;
my @interestIDs = ();
my %interestIDLocations;
my @hitsIDs = ();
##Argument
my $copsPath = '/mnt/project/pracstrucfunc12/data/COPS/COPS-ChainHierarchy.txt';
my $nochain = 0;
my $interestPath = './interestIds';
my $hitsPath = './union.finpdb';
########################
###Argument Handling####
########################
my $result = GetOptions(
'help|h|?' => sub { pod2usage( -verbose => 1 ); },
'man|m' => sub { pod2usage( -verbose => 2 ); },
'c|cops=s' => \$copsPath,
'nc|nocain' => \$nochain,
'i|interest=s' => \$interestPath,
'hi|hits=s' => \$hitsPath
) or pod2usage( -verbose => 1 ) && exit;
#Read IDs to look out for
my $fhi;
open( $fhi, '<', $interestPath );
while ( my $line = <$fhi> )
{
if ( $line =~ m/(\w{4},\w)/ || $line =~ m/(\w{4})/ )
{
my $iid = lc($1);
push( @interestIDs, $iid );
$interestIDLocations{$iid} = {};
}
}
close($fhi);
#Read ids that were found by prediction method(s)
my $fhh;
open($fhh, '<', $hitsPath);
while(my $line =<$fhh>)
{
if($line =~ m/^(\w{4})$/)
{
push(@hitsIDs, lc($1));
}
}
close($fhh);
print "Found # hits: " . scalar(@hitsIDs) . "\n";
#Parse the COPS structure
my $fh;
open( $fh, '<', $copsPath );
while ( my $line = <$fh> )
{
if ( $line =~ m/^Chain (.+)$/ )
{
#Header line found. Inititialize the cluster hash
my @matches = $1 =~ m/\w+/g;
for my $clusterName (@matches)
{
$clusters{$clusterName} = {};
}
@clusterOrder = @matches;
}
elsif ( $line =~ m/\w{4},/ )
{
#Cluster info line
my @matches = $line =~ m/(\w{4},\w)/g;
my $currentId = shift(@matches);
# print "current id is $currentId\n";
$currentId = sanitizePdbIDs($currentId);
my $count = 0;
for my $representative (@matches)
{
$representative = sanitizePdbIDs($representative);
my $currentCluster = $clusterOrder[ $count++ ];
# print "currentCluster is $currentCluster\n";
if ( !exists $clusters{$currentCluster} || !defined $clusters{$currentCluster} )
{
print "this should not have happened :)\n";
next;
}
if ( !exists $clusters{$currentCluster}{$representative} )
{
#Inititialize the cluster with the representative
$clusters{$currentCluster}{$representative} = [$representative];
}
#Add the current pdb id
if ( !( $currentId ~~ @{ $clusters{$currentCluster}{$representative} } ) )
{
#This case can only occur when we do not use the chains
push( @{ $clusters{$currentCluster}{$representative} }, $currentId );
}
if ( $currentId ~~ @interestIDs )
{
if(!defined $interestIDLocations{$currentId}{$currentCluster})
{
$interestIDLocations{$currentId}{$currentCluster}= ();
}
push(@{$interestIDLocations{$currentId}{$currentCluster} }, $representative);
}
}
}
}
close($fh);
#Do some maybe interesting output
for my $intId (@interestIDs)
{
printClustersForId($intId);
}
sub printClustersForId
{
my $id = shift;
my @allIn = ();
my @allOut = ();
for my $cluster ( sort(keys( $interestIDLocations{$id} ) ) )
{
my %clusterMembersMerged = ();
print "MEMBERS: $id -- $cluster : ";
my @currentRepresentatives = @{$interestIDLocations{$id}{$cluster}};
for my $currentRepresentative (@currentRepresentatives)
{
my @clusterMembers = @{ $clusters{$cluster}{$currentRepresentative} };
for my $member (@clusterMembers)
{
# print "$member ";
$clusterMembersMerged{$member} = ;
}
# print "\n";
}
my @clusterMembersMergedArr= keys(%clusterMembersMerged);
for my $e (@clusterMembersMergedArr)
{
print $e." ";
}
print "\n";
my $hitsIn = 0;
my $hitsOut = 0;
print "OVERLAPS: $id -- $cluster : ";
for my $hit (@hitsIDs)
{
if($hit ~~ @clusterMembersMergedArr)
{
$hitsIn++;
}
else
{
$hitsOut++;
}
}
print "In: $hitsIn, Out: $hitsOut\n";
push(@allIn, $hitsIn);
push(@allOut, $hitsOut);
}
#Write Out In/Out over Cluster stats for plotting in R
my $fho;
open($fho, '>', "stats$id.plotme");
for my $cluster (sort (keys( $interestIDLocations{$id})))
{
print $fho "\t$cluster";
}
print $fho "\n";
print $fho "IN";
for my $elem (@allIn)
{
print $fho "\t$elem";
}
print $fho "\n";
print $fho "OUT";
for my $elem (@allOut)
{
print $fho "\t$elem";
}
print $fho "\n";
close($fho);
}
sub sanitizePdbIDs
{
my $id = shift;
if ($nochain)
{
$id = substr( $id, 0, 4, );
}
return $id;
}
</source>
MSA
Dataset creation
<source lang="bash">
# Get details for the pdb proteins union grep -f pdbSets/union.finpdb m8blastpgpBIG_3800*.out > pdbunionBlast
</source>
Runs
<source lang="bash">
p="/mnt/home/student/meiera/1_SeqAli/2_MSA" export PATH=$PATH:/mnt/opt/T-Coffee/bin/
clustalw -align -infile=$p/datasets/msaset_40.fasta -outfile=$p/clustalw_msaset_40.aln clustalw -align -infile=$p/datasets/msaset_60.fasta -outfile=$p/clustalw_msaset_60.aln clustalw -align -infile=$p/datasets/msaset_all.fasta -outfile=$p/clustalw_msaset_all.aln clustalw -infile=$p/datasets/msaset_40.fasta -outfile=$p/clustalw_TESTmsaset_40.aln
muscle -in $p/datasets/msaset_40.fasta -out $p/muscle_msaset_40.msa -quiet muscle -in $p/datasets/msaset_60.fasta -out $p/muscle_msaset_60.msa -quiet muscle -in $p/datasets/msaset_all.fasta -out $p/muscle_msaset_all.msa -quiet
t_coffee $p/datasets/msaset_40.fasta -outfile $p/tcdef_40.aln t_coffee $p/datasets/msaset_60.fasta -outfile $p/tcdef_60.aln t_coffee $p/datasets/msaset_all.fasta -outfile $p/tcdef_all.aln t_coffee $p/datasets/msaset_40_struct.fasta -outfile $p/tcdef_40_struct.aln
t_coffee $p/datasets/msaset_40_struct.fasta -method pdb_pair -template_file $p/datasets/msa40struct.temp -outfile $p/tc3d_msa40struct.aln &> $p/tc3d_msa40struct.log </source>
The template file looks like this:
<source lang="bash"> >sp|P06865|HEXA_HUMAN Beta-hexosaminidase subunit alpha OS=Homo sapiens GN=HEXA PE=1 SV=2 _P_ 2gjxA >tr|Q06GJ0|Q06GJ0_OSTFU N-acetylglucosaminidase OS=Ostrinia furnacalis PE=1 SV=1 _P_ 3nsnA >tr|D0VX21|D0VX21_PAESP Beta-hexosaminidase OS=Paenibacillus sp. GN=Hex1 PE=1 SV=1 _P_ 3gh5A </source>
Plotting
Distribution of hits that full in and out of clusters
<source lang="bash">
library(gplots) #Needs caTools, bitops and a few more. Gives us: barplot2
cbarnames <- 2.5
clwd <- 5
clwdaxis <- 20
ccaxis <- 2
maindat <- read.table('stats2gjx.plotme')
mainmat <- as.matrix(maindat, header=TRUE)
lab <- c("IN", "OUT")
lab <- row.names(mainmat)
len <- length(lab)
method_col <- c("red", "blue")
png("./tsd_inoutdistri.png", height=800, width=800)
# par(xpd=T, mar=par()$mar+c(0,0,0,13))
barplot2(mainmat, beside=TRUE, col=method_col, cex.axis=ccaxis, cex.names=cbarnames, xpd=F, plot.ci=FALSE,cex.main=cbarnames, main="Overlap of union PDB hits with COPS Clusters") #names.arg=c("IN","OUT","IN","OUT","IN","OUT","IN","OUT","IN","OUT")
legend(4,70, lab, fill=method_col, cex=2, ncol=1)
par(mar=c(5, 4, 4, 2) + 0.1) # Restore default clipping rect
dev.off()
</source>
Overlap of PDB hits found by the different methods
<source lang="bash">
library("VennDiagram")
main1<-"Overlap of PDB hits"
sub1<-"BIG database"
hhb <- read.table("data/hhblits.finpdb")
psiit10e002 <- read.table("data/psiblastBIGit10e002.finpdb")
psiit10e10<-read.table("data/psiblastBIGit10e-10.finpdb")
psiit2e002<-read.table("data/psiblastBIGit2e002.finpdb") # psiit2e10<-read.table("data/psiblastBIGit2e-10.finpdb")
psi=list("HHblits"=hhb[,1], "It10, Ev10e-10"=psiit10e10[,1],"It10, Ev002"=psiit10e002[,1],"It2, Ev10e-10/Ev002"=psiit2e002[,1])
venn.diagram(psi,"pdbHitsOverlap.tif", scaled = TRUE,col=c("darkblue", "darkgreen", "orange","darkorchid4"), fill=c("cornflowerblue", "green", "yellow","darkorchid1"),
fontfamily = "serif", fontface = "bold", cat.col = c("darkblue", "darkgreen", "orange","darkorchid4"),cat.cex = 1.5, cat.pos = 0, cat.fontfamily = "serif",
rotation.degree = 200, main=main1, sub=sub1,main.cex=2,sub.cex=1.3,lwd=1,euler.d=2,lty=1, cat.dist=c(0.1,0.1,0.13,0.1))
</source>
e-Value and identity distributions
<source lang="bash">
ccmain <- 1.7
ccaxis <- 2
cclab <- 2
col1 <- "#0000ff"
col2 <- "#ff0000"
col3 <- "#00ff00"
col4 <- "#808080"
col1t <- "#0000FF80"
col2t <- "#FF000080"
col3t <- "#00ff0080"
col4t <- "#80808080"
###Blast
d <- read.table("./temp/blastall1200_IdEvfixed.plot")
d_id <- d$V1
d_ev <- d$V2
#Plot identities
png(width=600, height=600, "tsd_blastallIdent.png")
par(mar=par()$mar+c(0,1,-1,0))
hist(d_id, breaks=100,xlim=c(0,100), main="Blast - Histogram of identities",xlab="% sequence identity in Blast alignment", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1)
dev.off()
#Plot evalues
png(width=600, height=600, "tsd_blastallEval.png")
par(mar=par()$mar+c(0,1,-1,0))
hist(log(d_ev), breaks=100, main="Blast - Histogram of eValue distribution",xlab="log(eValue)", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1)
dev.off()
###Psi-Blast normal
d1 <- read.table("./temp/blastpgp1200_it2e002_IdEvfixed.plot")
d2 <- read.table("./temp/blastpgp1200_it10e002_IdEvfixed.plot")
d3 <- read.table("./temp/blastpgp1200_it2e-10_IdEvfixed.plot")
d4 <- read.table("./temp/blastpgp1200_it10e-10_IdEvfixed.plot")
d1_id <- d1$V1
d1_ev <- d1$V2
d2_id <- d2$V1
d2_ev <- d2$V2
d3_id <- d3$V1
d3_ev <- d3$V2
d4_id <- d4$V1
d4_ev <- d4$V2
lab = c("2 iterations, e002", "10 iterations, e002", "2 Iterations, 10e-10", "10 Iterations, 10e-10")
br <- seq(-450,0,5)
png("tsd_psiblastEvals_allfour.png", width=600, height=600)
par(mar=par()$mar+c(0,1,0,0))
hist(log(d1_ev), breaks=br, ylim=c(0,70), xlim=c(-450,0) ,main="PSI-Blast - Histogram of eValue distributions", xlab="log(eValue)", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1t)
mtext("BIG80 database", cex=1.4)
hist(log(d2_ev), breaks=br, ylim=c(0,70),xlim=c(-450,0) ,col=col2t, add=T)
hist(log(d3_ev), breaks=br, ylim=c(0,70),xlim=c(-450,0) ,col=col3t, add=T)
hist(log(d4_ev), breaks=br, ylim=c(0,70),xlim=c(-450,0) ,col=col4t, add=T)
legend("topright", lab, fill=c(col1t, col2t, col3t, col4t), cex=1.6, ncol=1)
dev.off()
lab = c("2 iterations, e002", "10 iterations, e002", "2 Iterations, 10e-10", "10 Iterations, 10e-10")
br <- seq(0,100,2.5)
png("tsd_psiblastIdents_allfour.png", width=600, height=600)
par(mar=par()$mar+c(0,1,0,0))
hist(d1_id, breaks=br , ylim=c(0,400),main="PSI-Blast - Histogram of identities", xlab="% sequence identity in Blast alignment", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1t)
mtext("BIG80 database", cex=1.4)
hist(d2_id, breaks=br,col=col2t, add=T)
hist(d3_id, breaks=br, col=col3t, add=T)
hist(d4_id, breaks=br, col=col4t, add=T)
legend("topright", lab, fill=c(col1t, col2t, col3t, col4t), cex=1.6, ncol=1)
dev.off()
###PSI-Blast BIG
d1 <- read.table("./temp/blastpgpBIG_3800_it2e002_IdEvfixed.plot")
d2 <- read.table("./temp/blastpgpBIG_3800_it10e002_IdEvfixed.plot")
d3 <- read.table("./temp/blastpgpBIG_3800_it2e-10_IdEvfixed.plot")
d4 <- read.table("./temp/blastpgpBIG_3800_it10e-10_IdEvfixed.plot")
d1_id <- d1$V1
d1_ev <- d1$V2
d2_id <- d2$V1
d2_ev <- d2$V2
d3_id <- d3$V1
d3_ev <- d3$V2
d4_id <- d4$V1
d4_ev <- d4$V2
lab = c("2 iterations, e002", "10 iterations, e002", "2 Iterations, 10e-10", "10 Iterations, 10e-10")
br <- seq(-450,0,5)
png("tsd_psiblastBIGEvals_allfour.png", width=600, height=600)
par(mar=par()$mar+c(0,1,0,0))
hist(log(d1_ev), breaks=br, ylim=c(0,260), xlim=c(-450,0) ,main="PSI-Blast - Histogram of eValue distributions", xlab="log(eValue)", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1t)
mtext("BIG database", cex=1.4)
hist(log(d2_ev), breaks=br, ylim=c(0,260),xlim=c(-450,0) ,col=col2t, add=T)
hist(log(d3_ev), breaks=br, ylim=c(0,260),xlim=c(-450,0) ,col=col3t, add=T)
hist(log(d4_ev), breaks=br, ylim=c(0,260),xlim=c(-450,0) ,col=col4t, add=T)
legend("topleft", lab, fill=c(col1t, col2t, col3t, col4t), cex=1.6, ncol=1)
dev.off()
lab = c("2 iterations, e002", "10 iterations, e002", "2 Iterations, 10e-10", "10 Iterations, 10e-10")
br <- seq(0,100,2.5)
png("tsd_psiblastBIGIdents_allfour.png", width=600, height=600)
par(mar=par()$mar+c(0,1,0,0))
hist(d1_id, breaks=br , ylim=c(0,1100),main="PSI-Blast - Histogram of identities", xlab="% sequence identity in Blast alignment", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1t)
mtext("BIG database", cex=1.4)
hist(d2_id, breaks=br,col=col2t, add=T)
hist(d3_id, breaks=br, col=col3t, add=T)
hist(d4_id, breaks=br, col=col4t, add=T)
legend("topright", lab, fill=c(col1t, col2t, col3t, col4t), cex=1.6, ncol=1)
dev.off()
###Hblits
d <- read.table("./temp/hhblits_460_P06865_IdEvfixed.plot")
d_id <- d$V1
d_ev <- d$V2
#Plot identities
png(width=600, height=600, "tsd_hhblitsIdent.png")
par(mar=par()$mar+c(0,1,-1,0))
hist(d_id, breaks=100, xlim=c(0,100), main="HHblits - Histogram of identities",xlab="% sequence identity in HHblits alignment", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1)
dev.off()
#Plot evalues
png(width=600, height=600, "tsd_hhblitsEval.png")
par(mar=par()$mar+c(0,1,-1,0))
hist(log(d_ev), breaks=100, main="HHblits - Histogram of eValue distribution",xlab="log(eValue)", cex.axis=ccaxis, cex.main=ccmain, cex.lab=cclab, col=col1)
dev.off()
</source> Boxplot for MSA gaps
<source lang="bash">
main1<-"Gaps in MSA"
png("testall.png")
boxplot(main=main1,col=c("blue","blue","blue","purple4","purple4","purple4","darkgreen","darkgreen","darkgreen"),names=c("<40%",">60%","Range", "<40%",">60%","Range", "<40%",">60%","Range"), clustal.m40,clustal.m60,clustal.mall,muscle.m40,muscle.m60,muscle.mall,tcoffee.m40,tcoffee.m60,tcoffee.mall,las=2)
legend("topleft",legend=c("ClustalW","Muscle","T-Coffee"),fill=c("blue","purple4","darkgreen"))
dev.off()
</source>
