fetchMGs 2.1.2

FetchMGs extracts the 40 marker genes from genomes and metagenomes in an easy and accurate manner.

fetchMGs (1.0 - 1.2) is copyright (c) 2019 Shinichi Sunagawa and Daniel R Mende.

fetchMGs (1.3) - written by Chris Field

fetchMGs (>=2.0) - written by Hans-Joachim Ruscheweyh

Introduction

Phylogenetic markers are genes (and proteins) which can be used to reconstruct the phylogenetic history of different organisms. One classical phylogenetic marker is the 16S ribosomal RNA gene, which is often-used but is also known to be a sub-optimal phylogenetic marker for some organisms. Efforts to find a good set of protein coding phylogenetic marker genes (Ciccarelli et al., Science, 2006; Sorek et al., Science, 2007) lead to the identification of 40 universal single copy marker genes (MGs). These 40 marker genes occur in single copy in the vast majority of known organisms and they were used to successfully reconstruct a three domain phylogenetic tree (Ciccarelli et al., Science, 2006).

What the software does

The program fetchMGs was written to extract the 40 MGs from genomes and metagenomes in an easy and accurate manner. This is done by utilizing Hidden Markov Models (HMMs) trained on protein alignments of known members of the 40 MGs as well as calibrated cutoffs for each of the 40 MGs. Please note that these cutoffs are only accurate when using complete protein sequences as input files. The output of the program are the protein sequences of the identified proteins, as well as their nucleotide sequences, if the nucleotide sequences of all complete genes are given as an additional input.

Installation

FetchMGs and all its dependencies can be installed via pip and have been tested with Python 3.12.

$pip install fetchMGs

Input

Users can submit genes in protein space or (from v2.0 on) genomes/metagenomes in nucleotide space.

Output

Per input sample (SAMPLE), fetchMGs will produce 3 output file:

1. SAMPLE.fetchMGs.faa --> the marker genes in protein space
2. SAMPLE.fetchMGs.fna --> the marker genes in nucleotide space
3. SAMPLE.fetchMGs.scores --> A link between marker genes and their bitscores

Full program help

$fetchMGs

Program: FetchMGs extracts the 40
    single copy universal marker genes (decribed in Ciccarelli et al.,
    Science, 2006 and Sorek et al., Science, 2007) from genomes and metagenomes
    in an easy and accurate manner.

    fetchMGs <command> [options]

      extraction     extract marker genes from sequences

    Type fetchMGs <command> to print the help menu for a specific command

Extraction

$fetchMGs extraction

Program: FetchMGs extracts the 40
    single copy universal marker genes (decribed in Ciccarelli et al.,
    Science, 2006 and Sorek et al., Science, 2007) from genomes and metagenomes
    in an easy and accurate manner.

    fetchMGs extraction input_file mode output_folder[options]

    Positional arguments:
         FILE        Input file - plain or gzipped. Can be either:
                        - A genome assembly file (NT), requires -m genome. Will 
                            call genes before marker gene extraction.
                        - A metagenome assembly file (NT), requires -m metagenome. Will 
                            call genes before marker gene extraction.
                        - A gene file in protein space (AA), requires -m gene. nucleotide 
                            sequences can be provided with -d parameter
                        - A text file with one line per input file. Requires 
                            -m parameter to enable "metagenome", "genome" or "gene" mode.
                            In "gene" mode another text file with samples in the
                            same order can be provided with -d parameter. 
        
        STR          Mode of extraction Values: [gene, genome, metagenome]
        
        FOLDER       Output folder for marker genes
        
    Input options:
       -d FILE       Nucleotide file/Text file. Enabled only in the "gene" mode.
                     Requires same order of sequence files if submitted as
                     text file.
                     

    Algorithm options:

       -t INT         Number of threads. Default=[1]
       -v             Report only the very best hit per COG and input file. Only useful 
                        if input files contain genes from genomes or are genomes.
          

Changelog

2.1.0

• No functional updates = produces the same output
• Commandline interface refactored.
  • fetchMGs expects 3 positional arguments, input_file, mode and output_folder
    • input_file: can be either a sequence file (genes in protein space, a genome or a metagenome) or a text file with one filepath per line to a genome/metagenome/protein file
    • mode: chose between gene (input file(s) are proteins), genome (input file(s) are genomes) or metagenome (input file(s) are metagenomes).
    • output_folder: The output folder
• Features:
  • Checks if the input file is a map file or a sequence file now based on file content instead of file endings
  • Checks if the input (and nucleotide) file(s) are in the right format. E.g. a nucleotide file is represented by a different alphabet compared to amino acid sequences.

2.0.1

• Changed automatic detection of input files to amino for pyhmmer
• allow users to submit a file with a list of input files for positional and -d parameters

2.0.0

• Calibration mode was removed
• hmmer and prodigal were replaced with pyhmmer and pyrodigal
• Input is more flexible. Users can now submit multiple files and use different input formats:
  • Genes (-m gene)
  • Genomes (-m genome)
  • Metagenomes (-m metagenome)
• Output folder was cleaned up. Only one nucleotide and one protein file are generated compared to 40 in previous versions

1.3.0

• FetchMGs was ported from Perl to Python 3