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Cédric Arisdakessian, Sean B. Cleveland, and Mahdi Belcaid. 2020. MetaFlow|mics: Scalable and Reproducible Nextflow Pipelines forthe Analysis of Microbiome Marker Data. InPractice and Experience in Advanced Research Computing (PEARC ’20), July 26–30, 2020,Portland, OR, USA.ACM, New York, NY, USA, 9 pages.
This repository is a collection of tools for 16S and ITS data analysis and was developed to support scientifics at the Pacific Biosciences Research Center <http://www.pbrc.hawaii.edu/>
to analyze microbial data.
This work was funded by the Hawaii Data Science Institute <http://datascience.hawaii.edu/>
.
Each analysis tool has been implemented using Nextflow <https://www.nextflow.io/docs/latest/getstarted.html>
_ to facilitate their use on any environment, and more specifically on a High Performance Computing Cluster or a Cloud service (GCP, AWS, ...). Some configurations are already available in the conf
folder (local, hpcc, google cloud). These configurations can be expanded for any other platform.
You will find three available app:
See the documentation <https://metagenomics-pipelines.readthedocs.io>
_ for more details.
GitHub <https://github.com/hawaiidatascience/metaflowmics/issues>
_GitHub <https://github.com/hawaiidatascience/metaflowmics/tree/master/metaflowmics>
_Apache 2.0