PconsC2 v1.0-beta2

PconsC2

Improved contact predictions using the recognition of protein like contact patterns.

Dependencies:

• NetSurfP 1.1
• PSIPRED v3.5
• Jackhmmer from HMMER v3.0 or higher
• HHblits from HHsuite v2.0.16
• PSICOV v1.11
• plmDCA asymmetric
• either MATLAB v8.1 or higher
• or MATLAB Compiler Runtime (MCR) v8.1

MATLAB is needed to run plmDCA. However, if MATLAB is not available you can also use a compiled version of plmDCA. For the compiled version to run you need to provide a path to MCR.

How to run it:

Make sure all dependencies are working correctly and adjust the paths in localconfig.py.

To run PconsC2 use:

./run_pconsc.py [-c n_cores] [-l n_layers] [--pconsc1]
             hhblits_database jackhmmer_database sequence_file

• Required:
  • hhblits_database and jackhmmer_database are paths to the databases used by HHblits and Jackhmmer
  • sequence_file is the path to the input protein sequence in FASTA format (only single sequences).
• Optional:
  • n_cores specifies the number of cores to use during computation (default: number of available cores).
  • n_layers is the number of layers of deep-learning being used (default: 5)
  • --pconsc1 flag runs PconsC1 instead of PconsC2

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PconsC2

PconsC2

Improved contact predictions using the recognition of protein like contact patterns.

Dependencies:

• NetSurfP 1.1
• PSIPRED v3.5
• Jackhmmer from HMMER v3.0 or higher
• HHblits from HHsuite v2.0.16
• PSICOV v1.11
• plmDCA asymmetric
• either MATLAB v8.1 or higher
• or MATLAB Compiler Runtime (MCR) v8.1

MATLAB is needed to run plmDCA. However, if MATLAB is not available you can also use a compiled version of plmDCA. For the compiled version to run you need to provide a path to MCR.

How to run it:

Make sure all dependencies are working correctly and adjust the paths in localconfig.py.

To run PconsC2 use:

./run_pconsc.py [-c n_cores] [-l n_layers] [--pconsc1]
             hhblits_database jackhmmer_database sequence_file

• Required:
  • hhblits_database and jackhmmer_database are paths to the databases used by HHblits and Jackhmmer
  • sequence_file is the path to the input protein sequence in FASTA format (only single sequences).
• Optional:
  • n_cores specifies the number of cores to use during computation (default: number of available cores).
  • n_layers is the number of layers of deep-learning being used (default: 5)
  • --pconsc1 flag runs PconsC1 instead of PconsC2

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