{"id":5185,"date":"2021-02-09T11:29:28","date_gmt":"2021-02-09T11:29:28","guid":{"rendered":"http:\/\/ri.itservices.manchester.ac.uk\/csf3\/?page_id=5185"},"modified":"2021-02-09T11:29:51","modified_gmt":"2021-02-09T11:29:51","slug":"eggnog-mapper","status":"publish","type":"page","link":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/software\/applications\/eggnog-mapper\/","title":{"rendered":"eggNOG mapper"},"content":{"rendered":"

Overview<\/h2>\n

EGGNog-Mapper<\/a> is a tool for fast functional annotation of novel sequences. It uses precomputed orthologous groups and phylogenies from the eggNOG database (http:\/\/eggnog5.embl.de<\/a>) to transfer functional information from fine-grained orthologs only.<\/p>\n

Version 2.0.5 is installed on the CSF.<\/p>\n

Restrictions on use<\/h2>\n

If you use the software please cite the two references given at: https:\/\/github.com\/eggnogdb\/eggnog-mapper\/wiki\/eggNOG-mapper-v2.0.2-v2.0.6#Citation<\/a><\/p>\n

Please note that the eggnog databases have been downloaded and installed centrally. You do not need your own copy. The modulefile (see below) will set up the path to these databases.<\/p>\n

Set up procedure<\/h2>\n

We now recommend loading modulefiles within your jobscript so that you have a full record of how the job was run. See the example jobscript below for how to do this. Alternatively, you may load modulefiles on the login node and let the job inherit these settings<\/abbr>.<\/p>\n

Load one of the following modulefiles:<\/p>\n

\r\nmodule load apps\/python\/eggnog-mapper\/2.0.5\r\n<\/pre>\n
You may run the following command on the login node to get help with the command-line flags:<\/p>\n
\r\nemapper.py --help\r\n<\/pre>\n
Running the application<\/h2>\n
Please do not run eggnog-mapper on the login node. Jobs should be submitted to the compute nodes via batch.<\/p>\n
Note that a serial (one-core) job may not give you enough memory to run eggnog-mappy (it gives you 4-5GB). The software is multi-core capable so we recommend using a parallel job (see below) which will speed up the software and give you more memory to work with (4-5GB per core).<\/p>\n
Serial batch job submission<\/h3>\n
Note that a serial (one-core) job may not give you enough memory to run eggnog-mappy (it gives you 4-5GB). The software is multi-core capable so we recommend using a parallel job (see below) which will speed up the software and give you more memory to work with (4-5GB per core).<\/p>\n
Create a batch submission script (which will load the modulefile in the jobscript), for example:<\/p>\n
\r\n#!\/bin\/bash --login\r\n#$ -cwd             # Job will run from the current directory\r\n                    # NO -V line - we load modulefiles in the jobscript\r\n\r\n# Load the version you require\r\nmodule load apps\/python\/eggnog-mapper\/2.0.5\r\n\r\nemapper.py --cpu $NSLOTS --scratch_dir ~\/scratch -i FASTA_FILE<\/em> -o resultsname<\/em>\r\n  #\r\n  # Add --output_dir dirname<\/em> to write results to a directory other than the current directory\r\n<\/pre>\n
Submit the jobscript using: <\/p>\n
qsub scriptname<\/em><\/pre>\n
where scriptname<\/em> is the name of your jobscript.<\/p>\n
Parallel batch job submission<\/h3>\n
Create a batch submission script (which will load the modulefile in the jobscript), for example:<\/p>\n
\r\n#!\/bin\/bash --login\r\n#$ -cwd             # Job will run from the current directory\r\n#$ -pe smp.pe 8     # Number of cores (can be 2--32)\r\n\r\n### You may wish to add a high-memory flag but this may limit the number of cores\r\n### #$ -l mem512\r\n\r\n# Load the version you require\r\nmodule load apps\/python\/eggnog-mapper\/2.0.5\r\n\r\nemapper.py --cpu $NSLOTS --scratch_dir ~\/scratch -i FASTA_FILE<\/em> -o resultsname<\/em>\r\n  #\r\n  # Add --output_dir dirname<\/em> to write results to a directory other than the current directory\r\n<\/pre>\n
Submit the jobscript using: <\/p>\n
qsub scriptname<\/em><\/pre>\n
where scriptname<\/em> is the name of your jobscript.<\/p>\n
Further info<\/h2>\n