Abstract: Advancement and accessibility of next-generation sequencing technologies have influenced microbiome analyses in tremendous ways, opening up applications in the areas of clinical, diagnostic, therapeutic, industrial, and environmental research. However, due to the complexity of 16S rRNA and metagenomic sequencing analysis, significant challenges can be posed by biases introduced during sample preparation, DNA extraction, PCR amplification, library preparation, sequencing, or data interpretation. One of the primary challenges in assay standardization is the limited availability of reference materials. To address these biases and provide a measure of standardization within microbiome research and applications, ATCC has developed a set of mock microbial communities comprising fully sequenced, characterized strains selected on the basis of phenotypic and genotypic attributes, such as cell wall type (Gram stain classification), GC content, genome size, unique cell wall characteristics, and spore formation. These mock communities mimic mixed metagenomic samples and offer a universal control for microbiome analyses and assay development. Moreover, these standards have been developed with different levels of mock community complexity (10 or 20 strains per community) with even or staggered relative abundance, including diverse strains that are relevant to a broad range of applications. In addition, to minimize the bias associated with data interpretation, we have developed a data analysis module in collaboration with One Codex. This module provides a user-friendly output in the form of true-positive, relative abundance, and false-negative scores for 16S rRNA community profiling and shotgun metagenomic sequencing.