Microbiome discovery efforts are underway in multiple disease areas.  Challenges exist in sample collection, processing, assay selection and bioinformatics.  Therefore heterogeneity exists in published findings for biomarkers.  Using the Amazon cloud and machine learning, sets of consistent biomarkers can be observed in biospecimens from diseased subjects that differentiate them from healthy controls.  The benefits of applying consistent assays with internal controls within each test will be discussed.  Since the same data collected for diagnostic discovery, also aids in therapeutic hypotheses generation, a platform that outputs both will be outlined.
 
Learning Objectives:
- Be able to list at least 2 disease areas where microbiome analyses are applied.
- Be able to list at least 2 sources of variation in biomarker discovery in microbiome analyses.
- Be able to identify the benefits of internal controls in evaluating assay value.