Difference between revisions of "Protocol"

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(GO terms)
(GO terms)
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== GO terms ==
 
== GO terms ==
   
To predict GO terms, the online server of [http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar GOPET] and [http://www.cbs.dtu.dk/services/ProtFun/ ProtFun2.0] were used. To confirm such the prediction results, [http://pfam.sanger.ac.uk/ Pfam] was used.
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To predict GO terms, the online server of [http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar GOPET] and [http://www.cbs.dtu.dk/services/ProtFun/ ProtFun2.0] were used. To confirm the prediction results, [http://pfam.sanger.ac.uk/ Pfam] was used.

Revision as of 09:01, 21 May 2012

Secondary structure

Sources

The data and scripts we used can be found in /mnt/home/student/angermue/mp/tasks/task03/ss

DSSP assignment

We simply used the DSSP server to get the DSSP secondary structure assignments.

PSIPRED

For calling PSIPRED, we adjusted the script runpsipred of the PSIPRED package. Three rounds PSI-BLAST were carried out to build the PSI-BLAST profile which is used as input of PSIPRED.

Reprof

We called the pre-installed Reprof program by reprof -i FASTA-SEQUENCE -o OUTPUT-FILE.

Further scripts

ss_format.pl Converts the output of DSSP, PSIPRED, or Reprof into a common output format with secondary structure states H, E, C.
ss_eval.pl Takes a reference and further ss_format.pl formatted files which are to be evaluated.
ss_viz.pl Visualizes several ss_format.pl formatted predictions-

Disorder

Sources

The data and scripts we used can be found in /mnt/home/student/angermue/mp/tasks/task03/disorder

IUPred

We called IUPred by:

iupred SEQ-FILE long

Further scripts

eval.pl Calculates the precision, sensitivity, and specificity given a set of predicted residues, reference residues and the length of the protein.

Transmembrane helices

At first, get all the sequences from Uniprot:

wget http://www.uniprot.org/uniprot/P04062.fasta
wget http://www.uniprot.org/uniprot/P35462.fasta
wget http://www.uniprot.org/uniprot/Q9YDF8.fasta
wget http://www.uniprot.org/uniprot/P47863.fasta

Then execute the following bash shell script to do prediction:

#!/bin/bash
#$ -S /bin/sh
IN=/mnt/project/pracstrucfunc12/data/index_pp/uniprot_sprot.idx
DB=/mnt/project/pracstrucfunc12/data/swissprot/uniprot_sprot
PATH=$PATH:/mnt/project/pracstrucfunc12/polyphobius/
export PATH

mkdir -p output/
for file in `ls | grep ".fasta"`; do
    `perl /mnt/project/pracstrucfunc12/polyphobius/blastget -db $DB -ix $IN $file > output/$file.blast`
     wait 
    `/mnt/opt/T-Coffee/bin/kalign -f fasta -input output/$file.blast -output output/$file.msa`
     wait 
    `perl /mnt/project/pracstrucfunc12/polyphobius/jphobius -poly output/$file.msa &> output/$file.phob`
     wait		
done

Signal peptides

The SignalP server with version 4.0 was used.

GO terms

To predict GO terms, the online server of GOPET and ProtFun2.0 were used. To confirm the prediction results, Pfam was used.