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OMAmo - orthology-based model organism selection

Project description

OMAMO: orthology-based model organism selection

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OMAMO is a tool that suggests the best model organism to study a biological process based on orthologous relationship between a species and human.

The user can consider several species as potential model organisms and the algorithm will rank them and report the output for a given biological process (searched as a GO term or a GO ID) is produced in the dataframe format.


Following Python packages are needed: numpy, matplotlib, pickle and pandas. Besides, you need to install pyOMA.


Firstly, download the OMA dataset:

wget  -O data/OmaServer.h5  #caution: 94GB

Secondly, using the file data/oma-species.txt find the five-letter UniProt code for species of interest. For example, consider three species Dicdyostelium discodeium , Neurospora crassa and Schizosaccharomyces pombe. Their UniProt codes are DICDI, NEUCR and SCHPO, respectively.

Install omamo from the git checkout:

pip install <path_to_omamo.git>

Once the package is installed, you should be able to run omamo as a command. With omamo -h see the available options:

usage: omamo [-h] --db DB [--query QUERY] [--ic IC] [--h5-out H5_OUT] [--tsv-out TSV_OUT] --models MODELS [MODELS ...]

Run omamo for a set of model organisms

optional arguments:
  -h, --help            show this help message and exit
  --db DB               Path to the HDF5 database
  --query QUERY         Name of the Query species, defaults to HUMAN
  --ic IC               Path to the information content file (tsv format)
  --h5-out H5_OUT       Path to the HDF5 output file. If omitted, not stored in this format
  --tsv-out TSV_OUT     Path to the TSV output file. If omitted, not stored in this format
  --models MODELS [MODELS ...]
                        List of model species, or a path to a txt file with the model species

In order to create the omamo data for Dicdyostelium discodeium, Neurospora crassa and Schizosaccharomyces pombe, we would run omamo with the following parameters:

omamo --db OmaServer.h5 --query HUMAN --tsv-out omamo_output_df.csv --models  DICDI NEUCR SCHPO

You might face an error about OSError: ``OmaServer.h5.idx`` does not exist and pyoma.browser.db.DBConsistencyError: Suffix index for protein sequences is not available which you can ignore them.

Finally, the output data frame is ready as a TSV file omamo_output_df.csv. For example, for the GO ID of GO0000472, "endonucleolytic cleavage to generate mature 5'-end of SSU-rRNA", OMAMO provides the following ranking for potential model organisms:

head -n 1 omamo_output_df.csv > ranked_organisms.csv
awk '$1 == 472'  omamo_output_df.csv >> ranked_organisms.csv
cat ranked_organisms.csv

GOnr	Species	QuerySpeciesGenes	ModelSpeciesGenes NrOrthologs	FuncSim_Mean	FuncSim_Std	Score
472	DICDI	NOP9;TBL3;ABT1	  Q551Y5;Q7KWS8;esf2	          3  	0.9095	0.1567	2.7286
472	NEUCR	NOP9;TBL3	         nop9;pod-5	          2  	1.0000	0.0000	2.0000
472	SCHPO	NOP9;TBL3	         nop9;utp13	          2  	1.0000	0.0000	2.0000

OMAMO Website

You can also visit the OMAMO website, where you can browse biological processes to study in 50 unicellular species.

Change log

Version 0.2.1

  • store ic values in hdf5 database

Version 0.2.0

  • Overhaul and creating pip package

Version 0.0.1

  • Initial release


Alina Nicheperovich, Adrian M Altenhoff, Christophe Dessimoz, Sina Majidian, "OMAMO: orthology-based model organism selection", submitted to Bioinformatics journal, preprint.


OMAMO is a free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

OMAMO is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with OMAMO. If not, see

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