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