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ABSTRACTXu, Zhaohui, AdvisorMcKay, RobertRoy, SankardasShotgun metagenomics has provided a relatively new and powerful approach to study the environmental samples to characterize the microbial communities in contrast to pure cultures by conventional techniques. To determine the microbial diversity and to understand the role of microbesin the ecosystem, quantitative studies are important whose values are comparable across differentstudies and samples. We have developed a statistical approach to microbial profiling which encompasses quantitative characterization and comparison of relative abundance of the microbes ina metagenome sample based on their signature sequences (unique k-mers). We demonstrated theutility of this approach by characterizing and quantifying the relative abundance of the microbes in4 different simulated metagenome samples (Comp_25, Comp_50, Comp_75, and Comp_100). Thesuffix of simulated metagenome name represents the gene content percentage of reporter species in the simulated metagenomes.The analysis of simulated metagenomes for data volume 6e9 and 6e10 furnish the informationabout the abundance of species by identifying the unique k-mers (signature sequences) of thesix reporter species B. licheniformis, L. brevis, L. fermentum, L. plantarum, P. ananatis, and P.vagans. Our developed approach has efficiently identified the abundance of 4 reporter speciesi.e. B. licheniformis, L. brevis, L. fermentum, P. ananatis whereas 2 species L. plantarum and P.vagans were overestimated in the simulated metagenomes. So, application of advanced statistics,refinement of the algorithm, and an increase in data volume would be our next steps to improvethe accuracy of our approach to estimate the ratio of species of a metagenome.