Running GOMAP

How to run GOMAP?

GOMAP is run in two steps using pipeline1.py and pipleine2.py. First part of the pipeline runs the Sequence-similarity methods and domain-based methods, and FANN-GO and PANNZER. It also runs the pre-processing steps for Argot2.5. Second part of the pipeline processes results from different methods and compiles the final GO annotation dataset from all differnt approaches. The main steps are given below.

  1. Add the protein fasta file to input/raw/
  2. Make necessary changes to the config.json file
  • Update the work_dir in the pipeline section
  • Update the input section
    • Give the correct input FASTA file name
    • If the fasta contains multiple transcripts per gene then put the fasta in the input/raw directory and set the raw_fasta parameter
    • If the fasta file contains only on transcript per gene put it in the input/filt directory, and set the fasta parameter
    • Update the species, inbred and version parameters for your species
  • [Optional] Update the seq-sim section
    • (All the files should be already processed in this section)
  • [Optional] Update the mix-meth section
    • (All the files and fields should be already set, except changes to database section for PANNZER )
  • [Optional] Update blast and hmmer sections
    • This is to enable the correct number cpu threads for these software
  • All other sections should only be updated if things have been drastically changed.
  1. execute python pipeline1.py config.json
  • The pipeline will generate a number of intermidiate output files
  • Especially the mixed-method tools will require the input fasta to be split into smaller chunks. the chunks will be numbered serially. (e.g. test.1.fa, test.2.fa)
  • Argot 2.5 tool will NOT be executed within the pipeline
  1. Submit the files in mixed-meth/argot2.5/blast and mixed-meth/argot2.5/hmmer using correct pairing
  2. Extract the Argot2.5 result files for each job, in the mixed-meth/argot2.5/results directory and rename with correct prefix
  • Argot2.5 names all results as argot_results_ts0.tsv so the file should be renamed correctly (e.g. test.1.tsv, test.2.tsv)
  • Please do not leave any other file in the argot2.5 results directory, otherwise it will influence certain metrics.
  1. execute python pipeline2.py config.json

What are the steps needed to setup the pipeline?

  1. Install dependencies
  2. Install required packages for R and Python
  • A shell script is provided to make the installation of the packages easy.
  • Run bash install/install_packages.sh from GOMAP directory
  • Users with a python2 virtual environment please activate before running the script
  1. Setup MySQL database for Pannzer
  • Create a database named pannzer
  • Create a user names pannzer and grant all privileges on the database pannzer
  • The password should be pannzer
  • If you decide to change any of this, please update the config.json [mix-meth.PANNZER.database] file accordingly.

How to run the GOMAP?

GOMAP is run in two steps using pipeline1.py and pipleine2.py. First part of the pipeline runs the Sequence-similarity methods and domain-based methods, and FANN-GO and PANNZER. It also runs the pre-processing steps for Argot2.5. Second part of the pipeline processes results from different methods and compiles the final GO annotation dataset from all differnt approaches. The main steps are given below.

  1. Add the protein fasta file to input/raw/
  2. Make necessary changes to the config.json file
  • Update the work_dir in the pipeline section
  • Update the input section
    • Give the correct input FASTA file name
    • If the fasta contains multiple transcripts per gene then put the fasta in the input/raw directory and set the raw_fasta parameter
    • If the fasta file contains only on transcript per gene put it in the input/filt directory, and set the fasta parameter
    • Update the species, inbred and version parameters for your species
  • [Optional] Update the seq-sim section
    • (All the files should be already processed in this section)
  • [Optional] Update the mix-meth section
    • (All the files and fields should be already set, except changes to database section for PANNZER )
  • [Optional] Update blast and hmmer sections
    • This is to enable the correct number cpu threads for these software
  • All other sections should only be updated if things have been drastically changed.
  1. execute python pipeline1.py config.json
  • The pipeline will generate a number of intermidiate output files
  • Especially the mixed-method tools will require the input fasta to be split into smaller chunks. the chunks will be numbered serially. (e.g. test.1.fa, test.2.fa)
  • Argot 2.5 tool will NOT be executed within the pipeline
  1. Submit the files in mixed-meth/argot2.5/blast and mixed-meth/argot2.5/hmmer using correct pairing
  2. Extract the Argot2.5 result files for each job, in the mixed-meth/argot2.5/results directory and rename with correct prefix
  • Argot2.5 names all results as argot_results_ts0.tsv so the file should be renamed correctly (e.g. test.1.tsv, test.2.tsv)
  • Please do not leave any other file in the argot2.5 results directory, otherwise it will influence certain metrics.
  1. execute python pipeline2.py config.json