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116 lines
3.9 KiB
Markdown
116 lines
3.9 KiB
Markdown
<p align="center">
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<img src="https://www.angus.org/Media/pages/ClipArt/graphics/cow_sniff_calf.gif" alt="Logo" width="275">
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</p>
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# Cow/calf Rumen Metagenomics Pipeline
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An end-to-end script to convert Illumina shotgun sequences and metadata into
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full-blown diversity tables and visualizations. Of course, it's focused on the
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rumen and dam/calf relationships, but is widely applicable to other systems.
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Written entirely during Spring Semester 2019 for work done in [Dr. Hannah
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Cunningham-Hollinger's lab][hollinger-lab] at the University of Wyoming,
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computed on UW's [ARCC High-performance servers][arcc-servers] and presented as
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a [poster] at the Western Section American Association of Animal Science annual
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meeting.
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## Prerequisites
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You will need access to the following commands/programs:
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- `metaxa2`, `metaxa2_ttt`, `metaxa2_dc` ([Metaxa2])
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- `Rscript` ([R])
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- `source activate` ([Miniconda])
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- `qiime`, `biom` (Install within [conda environment] named `qiime2`)
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If working on a HPC, contact your department to find out how to get access to
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these commands.
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## Usage
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Clone the script files
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```bash
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git clone https://github.com/MillironX/cowcalf-rumen-metagenomic-pipeline.git
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```
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Create a directory with all forward- and reverse- read files in it, named as
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`<SAMPLEID>_R1_001.fastq.gz` for forward-reads and `<SAMPLEID>_R2_001.fastq.gz`
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for reverse-reads. Add a [QIIME2-compatible metadata file][qiime2-metadata]
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named `metadata.tsv`, text files containing the minimum and maximum rarefaction
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values names `rarefaction.min.txt` and `rarefaction.max.txt` and copy all of the
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code files into it. It should look like
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```plaintext
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.
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├── sample1_R1_001.fastq.gz
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├── sample1_R2_001.fastq.gz
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├── sample2_R1_001.fastq.gz
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├── sample2_R2_001.fastq.gz
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├── ...
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├── sampleN_R1_001.fastq.gz
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├── sampleN_R2_001.fastq.gz
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├── metadata.tsv
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├── rarefaction.min.txt
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├── rarefaction.max.txt
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├── main.sh
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├── fastq-to-taxonomy.sh
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├── manipulatefeaturetable.R
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├── fetchmetadata.R
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├── sample-classifier.sh
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└── sample-regression.sh
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```
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### With Slurm
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These scripts are preconfigured for use with [Slurm] and [Lmod]. Everything is
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very basic, and should work on any Slurm configuration. Before use, be sure to
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replace the provided credentials with your own in `main.sh`,
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`fastq-to-taxonomy.sh`, `sample-classifier.sh`, and `sample-regression.sh`, then
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run
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```bash
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sbatch main.sh
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```
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### Without Slurm
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Edit `main.sh` and remove every call to `srun` (including its cli options),
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replace every instance of `$SLURM_NTASKS` with the number of parallel threads
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you wish to run, and comment out every line that starts `module load`. Then run
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```bash
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./main.sh
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```
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## Future Work
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This project is finished. It is meant to be a reference and an inspiration, but
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nothing more. I do not intend to update the code now (as embarrassing as it
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might be).
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## Known Issues
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- Miniconda now uses the `conda activate` command line instead of `source
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activate`
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## License
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Distributed under the MIT License. See `LICENSE` for more information.
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## Contact
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Thomas A. Christensen II - [@MillironX](https://gab.com/MillironX)
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Project Link:
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[https://github.com/MillironX/cowcalf-rumen-metagenomic-pipline](https://github.com/MillironX/cowcalf-rumen-metagenomic-pipline)
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[hollinger-lab]:
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https://www.uwyo.edu/anisci/personnel-directory/wyoming-faculty-and-staff/hannah-cunningham-hollinger/index.html
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[poster]: https://millironx.com/Academia#metagenomics [arcc-servers]:
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https://www.uwyo.edu/arcc/ [slurm]: https://slurm.schedmd.com/overview.html
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[qiime2-metadata]: https://docs.qiime2.org/2019.4/tutorials/metadata/ [R]:
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https://www.r-project.org/ [metaxa2]: https://microbiology.se/software/metaxa2/
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[Miniconda]: https://conda.io/en/master/miniconda.html [conda environment]:
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https://docs.qiime2.org/2019.4/install/native/#install-qiime-2-within-a-conda-environment
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[Lmod]: https://lmod.readthedocs.io/en/latest/index.html
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