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Widespread availability of next-generation sequencing (NGS) technologies has prompted a recent surge in interest in the microbiome. As a consequence, metagenomics is a fast-growing field in bioinformatics and computational biology. An important problem in analyzing metagenomic sequenced data is to identify the microbes present in the sample and figure out their relative abundances. In this article we propose a highly efficient algorithm dubbed as Hybrid Metagenomic Sequence Classifier (HMSC) todoi:10.1101/2020.10.01.321067 fatcat:alxnq4sip5e5dlsi2s4wvmtyrm