Snaq: A Dynamic Snakemake Pipeline for Microbiome Data Analysis With QIIME2

Attayeb Mohsen; Yi-An Chen; Rodolfo S Allendes Osorio; Chihiro Higuchi; Kenji Mizuguchi

doi:10.3389/fbinf.2022.893933

Snaq: A Dynamic Snakemake Pipeline for Microbiome Data Analysis With QIIME2

Front Bioinform. 2022 Jul 1:2:893933. doi: 10.3389/fbinf.2022.893933. eCollection 2022.

Authors

Attayeb Mohsen¹, Yi-An Chen¹, Rodolfo S Allendes Osorio¹, Chihiro Higuchi¹, Kenji Mizuguchi^{1

2}

Affiliations

¹ Artificial Intelligence Center for Health and Biomedical Research (ArCHER), National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan.
² Institute for Protein Research, Osaka University, Osaka, Japan.

Abstract

Optimizing and automating a protocol for 16S microbiome data analysis with QIIME2 is a challenging task. It involves a multi-step process, and multiple parameters and options that need to be tested and determined. In this article, we describe Snaq, a snakemake pipeline that helps automate and optimize 16S data analysis using QIIME2. Snaq offers an informative file naming system and automatically performs the analysis of a data set by downloading and installing the required databases and classifiers, all through a single command-line instruction. It works natively on Linux and Mac and on Windows through the use of containers, and is potentially extendable by adding new rules. This pipeline will substantially reduce the efforts in sending commands and prevent the confusion caused by the accumulation of analysis results due to testing multiple parameters.

Keywords: 16S; QIIME2; automation; microbiome; snakemake.