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Map genes and genome to the Global Microbial Gene Catalog (GMGC)

Project description


Install with conda PyPI version gmgc_mapper_test Number of downloads License: MIT

Command line tool to query the Global Microbial Gene Catalog (GMGC).


GMGC-mapper runs on Python 3.6-3.8 and requires prodigal to be available for genome mode.

Conda install

The easiest way to install GMGC-mapper is through bioconda, which will ensure all dependencies (including prodigal) are installed automatically:

conda install -c bioconda gmgc-mapper

pip install

Alternatively, GMGC-mapper is available from PyPI, so can be installed through pip:

pip install GMGC-mapper

Note that this does not install prodigal (which is necessary for the genome-based workflow).

Install from source

Finally, especially if you are retrieving the cutting edge version from Github, you can install with the standard

python install


  1. Input is a genome sequence.
gmgc-mapper -i input.fasta -o output
  1. Input is DNA/protein gene sequences
gmgc-mapper --nt-genes genes.fna --aa-genes genes.faa -o output

The nucleotide input is optional (but should be used if available so that the quality of the hits can be refined):

gmgc-mapper --aa-genes genes.faa -o output

If yout input is a metagenome, you can use NGLess for assembly and gene prediction. For more details, read the docs.


The output folder will contain

  1. Outputs of gene prediction (prodigal).
  2. Complete data table, listing all the hits in GMGC, per gene.
  3. Complete table, listing all the genome bins (MAGs) that are found in the results.
  4. Human readable summary.

For more details, read the docs. A description of the outputs is also written to output folder for convenience.


  • -i/--input: path to the input genome file(.fasta/.gz/.bz2).

  • -o/--output: Output directory (will be created if non-existent).

  • --nt-genes: path to the input DNA gene file(.fasta/.gz/.bz2).

  • --aa-genes: path to the input Protein gene file(.fasta/.gz/.bz2).

Project details

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GMGC-mapper-0.2.0.tar.gz (13.7 kB view hashes)

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