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Check List for 16S-based Microbiome Analysis

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A reliable database is frequently updated, and most importantly, it is systematically organized by best practices with regards to taxonomic classification of prokaryotic organisms. This allows accurate species-level ID of far more sequencing reads than possible with public crowd-sourced 16S databases.

When trying to answer the essential question of “Who is there?” in a complex microbial community, it is necessary to understand what is required for best practices in bacterial community analysis.

 

  1. Are you using an up-to-date and qualified database?

Does it provide current taxonomic information from phylum to species or does it leave you hanging at the genus level or higher?

 

  1. Normalization

Is the 16S  gene copy number available for correction for all statistical calculations? The 16S gene copy number in gut bacteria, for example, can vary as much as 2-5 times. Such differences can be normalized by using an up-to-date microbial genome database which includes the gene copy number information for over 6,000 species. Species-level abundance measurements within communities are far more accurate when normalized for 16S copy number.

 

  1. Taxonomic biomarker discovery function

Can you find significant taxonomic biomarkers at the species-level?

 

  1. Functional prediction.

Can you predict the functions and metabolic pathways of each species from 16S rRNA data?

To obtain higher accuracy, it is recommended to predict them using information from over 10,000 whole genomes.

 

  1. Pre-loaded public microbiome data

With only a few clicks, you can compare your data to over 20,000 public data sets including the Human Microbiome Project and genomes from publications.

 

  1. Compatibility of various 16S region data

Is your database optimized to compare data from various 16S rRNA regions (e.g. V1V3, V4, or the full 16S genes)?

 

  1. Comparative analysis within a few minutes

Can you obtain and visualize results from filtering, and grouping hundreds of samples, with statistical validation for alpha/beta diversity and biomarker discovery within a few minutes?

 

* Our bioinformatics tool for 16S microbiome profiling is enhanced by EzBioCloud database which covers all the checklists mentioned above.

 

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