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Protein fold recognition using strucutal and sequence template threading
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psipred/pGenTHREADER
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############################################################################### # # README created 10/02/2009 # # INSTALL and test instructions for pGen/DomTHREADER # VERSION 8.9 # Author: [email protected] [email protected] # # Change in 8.9 # - addition of mtx2con # - Added predict_contacts.pl to bin/ # - added svm probability_model to data/ # # Changes in 8.7 # - fixes the psuedo-multialignment building scripts in BLAST+/ # # Changes in 8.6 # - consolidation of BLAST+scripts # - new genthreader.sh script for both domthreader and genthreader for BLAST+ # # Changes in 8.5 # - Some minor bug fixes to the BLAST+ methods # - Added the ability to switch off psiblast in the MSA methods when seeded # with the complete set of homologues # # Changes in 8.4 # - Several bug fixes for the MSA methods # # Changes in 8.3 # - Addition of MSA and BLAST+ methods # # Changes in 8.3.1 # - Ligand contact prediction removed # # Changes in 8.3.2 # - Ansible installer added # ############################################################################### INSTALLATION VIA GITHUB AND ANSIBLE: First ensure that ansible and PSIPRED are installed on your system, then clone the github repo. PSIPRED is available at https://github.com/psipred/psipred. Use the ansible installer provided for PSIPRED. For pGenTHREADER % pip install ansible % git clone https://github.com/psipred/pGenTHREADER.git % cd pGenTHREADER/ansible_installer Next edit the the config_vars.yml to reflect where you would like pGenTHREADER and its underlying data to be installed. The app_locations variable MUST be the same as you used for the PSIPRED install. You can choose a version of uniref but we recommend uniref90 for most accurate results. You can now run ansible as per % ansible-playbook -i hosts install.yml You can edit the hosts file to install pGenTHREADER on one or more machines. Manual installation can be completed with the steps below Follow the steps: #-----------------------------------------------------------------------------# # # Untar and install the fold libraries # #-----------------------------------------------------------------------------# 1. cd into tdb directory prompt> cd tdb 2. unpack the fold libraries prompt/tdb> tar -xvzf cath_tdb.tgz fold_lib.tar.gz NOTE: At present there is no software available to create fold libraries, but up to date libraries can be downloaded from our site. Support for user-created fold libraries will be added in a future release. #------------------------------------------------------------------------------ # # Build the binaries for your system # #------------------------------------------------------------------------------ 3. cd into the src directory 4. run the makefile prompt/src> make 5. install the compiled binary prompt/src> make install #------------------------------------------------------------------------------ # # Configure the shell script for your system # # #------------------------------------------------------------------------------ 6. cd back to the top level directory 7. open the shell script pGenThreader.sh in an editor 8. change the paths at the top to suit your install 9. install PSIPRED and NCBI BLAST if you haven't already (these are NOT included in this package). #------------------------------------------------------------------------------ # # Run the test jobs # # #------------------------------------------------------------------------------ 9. prompt> sh pGenThreader.sh pgen_test test/test.fsa 10.prompt> sh pDomThreader.sh pdom_test test/test.fsa 11.prompt> sh GenThreader.sh -j test -i test/test.fsa #------------------------------------------------------------------------------ # # Example outputs # # #------------------------------------------------------------------------------ 11. Compare your ouputs with the examples found within the test directory : test/pGT.output and test/pDT.output #------------------------------------------------------------------------------ # # Trouble shooting # # #------------------------------------------------------------------------------ 1. Check with your system administrator that you have installed the binaries correctly and that you have configured the shell scripts appropriately for your system 2. Send a polite Email to one of the GenThreader team: or alternatively try [email protected] if you are desperate! 3. Confused about the BLAST database to use? We recommend any large, relatively sequence complete non-redundant protein database. Uniref90 is a good choice. You may also wish to download pfilt to mask low complexity and repetative sequences in the database. #------------------------------------------------------------------------------ # # Experimental BLAST+, mutliple alignment and contact prediction support # #------------------------------------------------------------------------------ 1. /BLAST+ now contains a script for running pGenTHREADER and pDomTHREADER with BLAST+; GenThreader.sh. This requires the new chkparse code which you should find in src/ and bin/ 2. Copy then run this script from the root genTHREADER directory not from the BLAST+/ directory. 3. GenThreader.sh will take multiple sequence alignments input. This functionality only works with BLAST+. Takes optional command line variables which indicate if the msa is Complete (includes all relevant close and distant relatives); Partial (includes all relevant close relavties but no distant relatives) or Seed (does not include all relevant close or distant relatives) 4. Output of multiple alignments: This requires a copy of MAFFT is installed. You must change the MAFFT_DIR global variable at the top of the mafft_spliced_alignment.pl script to the path to your mafft bin/ directory. 5. The GenThreader.sh script can be set to output a map of the known ligand contacts in the genthreader hits, using the -c command line parameter. This output has the name contactcons. This will also output jalview input files for each pairwise alignment in the genthreader results. There can be found in jalview_inputs
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Protein fold recognition using strucutal and sequence template threading
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