Microbiomic research has grown in popularity in recent decades. The widespread use of next-generation sequencing technologies, including 16S rRNA gene-based and metagenomic shotgun-based methods, has produced a wealth of microbiome data. At present, most software and analysis workflows for analysis and processing of microbiomic data are command line-based, which requires considerable computing time and makes interaction difficult. Results To provide a command-line free, integrated, user

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... e friendly and online/local deployable microbiome analysis tool, we developed Microbiome Automated Analysis Workflows (MAAWf). The MAAWf assesses taxonomy, protein-coding genes, metabolic pathways, carbohydrate-active enzymes (CAZy) and antibiotic resistance genes (ARGs) for WMS, and clusters operational taxonomic units, alpha-/beta-diversity and functional annotations for 16S. MAAWf generates similar results to currently popular tools, but the running time was much shorter. MAAWf is freely accessible and source code available at http://www.maawf.com. Conclusions MAAWf is a visual, integrated, rapid analysis tool that enables remote and local computing of microbiome data. Background Microbiome sequencing is a powerful approach for studying microbial communities by nonculture methods, promoting microbiomic research such as the Human Microbiome Project (HMP), METAgenomics of the Human Intestinal Tract (MetaHIT), Metagenomics and