gbintk 1.0.0

gbintk (GraphBin-Tk): Assembly graph-based metagenomic binning toolkit

GraphBin-Tk: assembly graph-based metagenomic binning toolkit

GraphBin-Tk combines assembly graph-based metagenomic bin-refinement and binning techniques GraphBin, GraphBin2 and MetaCoAG along with additional processing functionality to visualise and evaluate results, into one comprehensive toolkit.

For detailed instructions on installation and usage, please refer to the documentation hosted at Read the Docs.

NEW: GraphBin-Tk is now available on bioconda and PyPI.

Installing GraphBin-Tk

Using conda

You can install GraphBin-Tk using the bioconda distribution. You can download conda from Anaconda or Miniconda. You can also use mamba instead of conda.

# add channels
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge

# create conda environment
conda create -n gbintk

# activate conda environment
conda activate gbintk

# install gbintk
conda install -c bioconda gbintk

# check gbintk installation
gbintk --help

Using pip

You can install GraphBin-Tk using pip from the PyPI distribution.

# install gbintk
pip install gbintk

# check gbintk installation
gbintk --help

For development

Please follow the steps below to install gbintk using flit for development.

# clone repository
git clone https://github.com/metagentools/gbintk.git

# move to gbintk directory
cd gbintk

# create and activate conda env
conda env create -f environment.yml
conda activate gbintk

# install using flit
flit install -s --python `which python`

# test installation
gbintk --help

Available subcommands in GraphBin-Tk

Run gbintk --help or gbintk -h to list the help message for GraphBin-Tk.

Usage: gbintk [OPTIONS] COMMAND [ARGS]...

  gbintk (GraphBin-Tk): Assembly graph-based metagenomic binning toolkit

Options:
  -v, --version  Show the version and exit.
  -h, --help     Show this message and exit.

Commands:
  graphbin   GraphBin: Refined Binning of Metagenomic Contigs using...
  graphbin2  GraphBin2: Refined and Overlapped Binning of Metagenomic...
  metacoag   MetaCoAG: Binning Metagenomic Contigs via Composition,...
  prepare    Format the initial binning result from an existing binning tool
  visualise  Visualise binning and refinement results
  evaluate   Evaluate the binning results given a ground truth

Citation

If you use GraphBin-Tk in your work, please cite the relevant tools.

GraphBin

Vijini Mallawaarachchi, Anuradha Wickramarachchi, Yu Lin. GraphBin: Refined binning of metagenomic contigs using assembly graphs. Bioinformatics, Volume 36, Issue 11, June 2020, Pages 3307–3313, DOI: https://doi.org/10.1093/bioinformatics/btaa180

GraphBin2

Vijini G. Mallawaarachchi, Anuradha S. Wickramarachchi, and Yu Lin. GraphBin2: Refined and Overlapped Binning of Metagenomic Contigs Using Assembly Graphs. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 8:1-8:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020). DOI: https://doi.org/10.4230/LIPIcs.WABI.2020.8

Mallawaarachchi, V.G., Wickramarachchi, A.S. & Lin, Y. Improving metagenomic binning results with overlapped bins using assembly graphs. Algorithms Mol Biol 16, 3 (2021). DOI: https://doi.org/10.1186/s13015-021-00185-6

MetaCoAG

Mallawaarachchi, V., Lin, Y. (2022). MetaCoAG: Binning Metagenomic Contigs via Composition, Coverage and Assembly Graphs. In: Pe'er, I. (eds) Research in Computational Molecular Biology. RECOMB 2022. Lecture Notes in Computer Science(), vol 13278. Springer, Cham. DOI: https://doi.org/10.1007/978-3-031-04749-7_5

Vijini Mallawaarachchi and Yu Lin. Accurate Binning of Metagenomic Contigs Using Composition, Coverage, and Assembly Graphs. Journal of Computational Biology 2022 29:12, 1357-1376. DOI: https://doi.org/10.1089/cmb.2022.0262

Funding

GraphBin-Tk is funded by an Essential Open Source Software for Science Grant from the Chan Zuckerberg Initiative.