MarkerMAG
Linking MAGs with 16S rRNA marker genes
Install / Use
/learn @songweizhi/MarkerMAGREADME
MarkerMAG: linking MAGs with 16S rRNA marker genes using paired-end short reads
Publication
- Weizhi Song, Shan Zhang, Torsten Thomas*, MarkerMAG: linking metagenome-assembled genomes (MAGs) with 16S rRNA marker genes using paired-end short reads, Bioinformatics, 2022, btac398, https://doi.org/10.1093/bioinformatics/btac398
- Contact: Dr. Weizhi Song (songwz03@gmail.com), Prof. Torsten Thomas (t.thomas@unsw.edu.au)
- Center for Marine Science & Innovation, University of New South Wales, Sydney, Australia
Updates
- 2022-05-08 - MarkerMAG is now available on Bioconda, please refers to "How to install" for details.
- 2022-03-12 - A demo dataset (together with command) has now been provided! You can use it to check if MarkerMAG is installed successfully on your system.
MarkerMAG modules
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Main module
link: linking MAGs with 16S rRNA marker genes
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Supplementary modules
How to install
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MarkerMAG is implemented in python3, It has been tested on Linux and MacOS, but NOT on Windows.
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A Conda package that automatically installs MarkerMAG's third-party dependencies (except Usearch :warning:) is now available. Please note that you'll need to install Usearch on your own as it's not available in Conda due to license issue.
# install with conda create -n MarkerMAG_env -c bioconda MarkerMAG # To activate the environment conda activate MarkerMAG_env # MarkerMAG is ready for running now, type "MarkerMAG -h" for help # To leave the environment conda deactivate -
It can also be installed with pip. Software dependencies need to be in your system path in this case. Dependencies for the
linkmodule include BLAST+, Barrnap, seqtk, Bowtie2, Samtools, HMMER, metaSPAdes and Usearch. Dependencies for the supplementary modules are provided in their corresponding manual page.# install with pip3 install MarkerMAG # upgrade with pip3 install --upgrade MarkerMAG -
Here are some example commands for UNSW Katana users.
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:warning: If you clone the repository directly off GitHub you might end up with a version that is still under development.
How to run
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MarkerMAG’s input consists of
- A set of user-provided MAGs
- A set of 16S rRNA gene sequences (either user-provided or generated with the
matam_16smodule) - Input reads need to be quality-filtered and in fasta format (no quality score).
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:warning: MarkerMAG is designed to work with paired short-read data (i.e. Illumina). It assumes the id of reads in pair in the format of
XXXX.1andXXXX.2. The only difference is the last character. You can rename your reads with MarkerMAG'srename_readsmodule (manual). -
Although you can use your preferred tool to reconstruct 16S rRNA gene sequences from the metagenomic dataset, MarkerMAG does have a supplementary module (
matam_16s) to reconstruct 16S rRNA genes. Please refer to the manual here if you want to give it a go. -
Link 16S rRNA gene sequences with MAGs (demo dataset):
MarkerMAG link -p Demo -r1 demo_R1.fasta -r2 demo_R2.fasta -marker demo_16S.fasta -mag demo_MAGs -x fa -t 12
Output files
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Summary of identified linkages at genome level:
| Marker | MAG | Linkage | Round | |:---:|:---:|:---:|:---:| | matam_16S_7 | MAG_6 | 181| Rd1 | | matam_16S_12 | MAG_9 | 102| Rd1 | | matam_16S_6 | MAG_59| 55 | Rd2 |
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Summary of identified linkages at contig level (with figure):
|Marker___MAG (linkages) |Contig |Round_1 |Round_2 | |:---:|:---:|:---:|:---:| |matam_16S_7___MAG_6(181) |Contig_1799 |176 |0 | |matam_16S_7___MAG_6(181) |Contig_1044 |5 |0 | |matam_16S_12___MAG_9(102) |Contig_840 |102 |0 | |matam_16S_6___MAG_59(39) |Contig_171 |0 |55 |

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Copy number of linked 16S rRNA genes.
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Visualization of individual linkage.
MarkerMAG supports the visualization of identified linkages (needs Tablet). Output files for visualization (example) can be found in the [Prefix]_linkage_visualization_rd1/2 folders. You can visualize how the linking reads are aligned to MAG contig and 16S rRNA gene by double-clicking the corresponding ".tablet" file. Fifty Ns are added between the linked MAG contig and 16S rRNA gene.

*If you saw error message from Tablet that says input files format can not be understood, please refer to here for a potential solution.
