Metagenomics Data Analysis Services

16S / ITS Amplicon Sequencing & Microbiome Profiling

This service provides high resolution taxonomic profiling of bacterial and fungal communities through targeted amplicon sequencing. It transforms raw sequencing reads into robust biological insights by resolving community composition, detecting subtle shifts in microbial diversity, and identifying candidate biomarker taxa. Designed for academic and research settings, the analysis supports studies in environmental microbiology, agricultural soils, host associated ecosystems, and basic microbial ecology. The approach delivers statistically rigorous, publication ready results that accelerate hypothesis testing and comparative community

16S / ITS Amplicon Sequencing & Microbiome Profiling

Overview

16S and ITS amplicon analysis characterizes microbial diversity from targeted sequencing data. The process begins with quality filtered reads that are clustered into amplicon sequence variants (ASVs) or operational taxonomic units (OTUs) using reference databases such as SILVA and UNITE. Diversity metrics including alpha richness and beta dissimilarity are calculated using compositional-aware normalization methods (e.g., CLR or CSS) to preserve data integrity, accompanied by ordination methods like principal coordinate analysis. Differential abundance testing identifies taxa that vary across experimental conditions, while functional predictions can be inferred from the taxonomic profiles (noting that inference accuracy depends on reference genome availability in the target habitat). Outputs include interactive visualizations, taxonomic summary tables, and sequence files suitable for downstream research.

Key Features

✓ End to end pipeline from quality control to ASV/OTU clustering (DADA2, QIIME2, UNOISE).
✓ Alpha & beta diversity metrics with interactive PCoA/NMDS ordination.
✓ Differential abundance analysis (DESeq2, ANCOM BC) and LEfSe biomarker discovery.
✓ Functional prediction from amplicon data (PICRUSt2, Tax4Fun2, FUNGuild).

Demo & Results

We analyzed 150 rhizosphere samples across three farming regimes and identified 23 bacterial genera significantly enriched under organic management. The microbial signatures guided the design of a synthetic consortium that improved crop yield by 12% in subsequent field trials.

Frequently Asked Questions