All dependencies are installed via conda using the bioconda channel. The workflow and some dependencies require Python 3.5.
To install:
conda install -c bioconda \
bbmap diamond fastqc megahit prodigal \
samtools snakemake spades subread
Maxbin2 and MEGAHIT for macOS are not current in the bioconda channel. For those dependencies, we've made them available to install as:
conda install -c brwnj maxbin2
Not necessary, but this can isolate ATLAS dependencies in a separate work
environment. Using environment.yml
:
conda env create -f environment.yml
And load and unload that environment using source activate atlas_env
and source deactivate atlas_env
, respectively.
Finally, from within the 'atlas' source folder:
python setup.py install
Following install, atlas
should be executable:
$ atlas -h
Usage: atlas [OPTIONS] COMMAND [ARGS]...
ATLAS
Options:
--version Show the version and exit.
-h, --help Show this message and exit.
Commands:
assemble assembly workflow
download download reference files
make-config prepopulate a configuration file with samples and defaults
ATLAS will soon be pushed to the Anaconda Cloud for easier install.
After installing, one needs to download the required databases and create a sample configuration file.
To download the databases and their respective metadata databases:
atlas download -o /databases
The downloads use approximately 40 GB of disk space.
To create a simple configuration file (which you can later edit), run:
atlas make-config --database-dir /databases config.yaml /my-data
In this case, 'my-data' is a directory containing .fastq files similar to:
$ tree /my-data
/my-data/
├── Sample-1_R1.fastq.gz
├── Sample-1_R2.fastq.gz
├── Sample-2_R1.fastq.gz
└── Sample-2_R2.fastq.gz
Paired-end, single-end (though some file names still suggest otherwise), and interleaved paired-end FASTQs are supported.
After editing your configuration file and adjusting any additional parameters we run assemblies across our samples using:
atlas assemble config.yaml
By default, this will write results into our current working directory across the total number of CPU cores available.
If you are publishing results obtained using ATLAS, please cite:
Richard Allen White III, Joseph Brown, Sean Colby, Christopher C. Overall, Joon-Yong Lee, Jeremy Zucker, Kurt R. Glaesemann, Christer Jansson, Janet K Jansson. ATLAS (Automatic Tool for Local Assembly Structures) - a comprehensive infrastructure for assembly, annotation, and genomic binning of metagenomic and metatranscriptomic data. PeerJ Preprints 5:e2843v1 https://doi.org/10.7287/peerj.preprints.2843v1.
Richard Allen White III, Joseph Brown, Sean Colby, Christopher C. Overall, Joon-Yong Lee, Jeremy Zucker, Kurt R. Glaesemann, Christer Jansson, Janet K Jansson. ATLAS (Automatic Tool for Local Assembly Structures) - a comprehensive infrastructure for assembly, annotation, and genomic binning of metagenomic and metatranscriptomic data. Bioinformatics. Submitted.
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