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The study of 16s rRNA sequences through Next Generation Sequencing (NGS) have revolutionized the understanding of the microbial community composition and its structure. The massive data production and substantial cost reduction in NGS technologies have led to rapid growth of metagenomic research both quantitatively and qualitatively. Soil Metagenomics is a discipline that enables the genomic study of uncultured organisms in the soil samples. Quantitative Insights Into Microbial Ecology (QIIME) and Cloud Virtual Resource (CloVR) processes metagenomic data from a high-throughput 16S rRNA sequencing platform, beginning with multiplexed sequence reads, then Operational taxonomic units picking, Summarizing taxonomies, phylogenetic relationships and analyzing the alpha and finally beta diversities through plots. The proposed study demonstrates the analysis of microbial composition present in the study sample using QIIME and CloVR metagenomic pipelines. The soil metagenomic Datasets applied for the present study are retrived from European Nucleotide Archive (ENA) under the sample ID ERP001958.The interrealtionships among the OTUs is studied through the network analysis. A comparative analysis of the metagenomic pipelines is also performed with the gene clustering algorithms for understanding the concept of OUT clustering in metagenomic analysis. This research underscores the usefulness of next-generation sequencing techniques both to understand the ecological impact of contamination and to identify potential molecular proxies for detection of natural attenuation.
