BOOM
If a lab used standard reference range process (and data was a normal distribution). There should be the same percentage being low and high. Ideally, 2.5% of samples in each group.
| Bacteria | Rank | Extremely Low Or None | Very Low | Low | Normal | High | Very High | Extremely High |
|---|---|---|---|---|---|---|---|---|
| Clostridia | class | 0 | 0.36 | 0 | 99.28 | 0.36 | 0 | 0 |
| Methanobacteriaceae | family | 0 | 0 | 0 | 99.28 | 0.72 | 0 | 0 |
| Bacteroides | genus | 0 | 0 | 0 | 99.64 | 0.36 | 0 | 0 |
| Barnesiella | genus | 0.72 | 0 | 0.72 | 97.83 | 0.72 | 0 | 0 |
| Bifidobacterium | genus | 0 | 0.72 | 1.09 | 97.1 | 1.09 | 0 | 0 |
| Campylobacter | genus | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Citrobacter | genus | 0.36 | 0 | 0 | 97.46 | 0 | 1.81 | 0.36 |
| Clostridium | genus | 0 | 0.36 | 0.36 | 97.83 | 1.09 | 0 | 0.36 |
| Collinsella | genus | 0.36 | 0 | 0 | 99.28 | 0.36 | 0 | 0 |
| Enterobacter | genus | 0.36 | 0 | 0 | 99.28 | 0 | 0.36 | 0 |
| Escherichia | genus | 0.72 | 0 | 0 | 98.91 | 0.36 | 0 | 0 |
| Fusobacterium | genus | 2.9 | 0 | 0.36 | 96.74 | 0 | 0 | 0 |
| Klebsiella | genus | 0.36 | 0 | 0 | 98.91 | 0 | 0.72 | 0 |
| Lactobacillus | genus | 1.81 | 0 | 0.36 | 97.1 | 0.72 | 0 | 0 |
| Odoribacter | genus | 1.45 | 0 | 1.09 | 96.74 | 0.72 | 0 | 0 |
| Prevotella | genus | 0 | 0.36 | 1.09 | 97.83 | 0.36 | 0.36 | 0 |
| Proteus | genus | 0 | 0 | 0.36 | 99.64 | 0 | 0 | 0 |
| Pseudoflavonifractor | genus | 0 | 0 | 0.72 | 98.55 | 0.72 | 0 | 0 |
| Roseburia | genus | 0 | 1.09 | 1.09 | 96.74 | 1.09 | 0 | 0 |
| Ruminococcus | genus | 0 | 0.36 | 0 | 98.91 | 0.72 | 0 | 0 |
| Salmonella | genus | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Shigella | genus | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Streptococcus | genus | 0 | 0 | 0 | 98.55 | 0.36 | 1.09 | 0 |
| Veillonella | genus | 0.36 | 0.36 | 0 | 98.19 | 1.09 | 0 | 0 |
| Actinomycetota | phylum | 0 | 0 | 1.09 | 98.19 | 0.72 | 0 | 0 |
| Bacillota | phylum | 0.36 | 0 | 0 | 98.91 | 0.72 | 0 | 0 |
| Bacteroidota | phylum | 0 | 0.36 | 0 | 99.64 | 0 | 0 | 0 |
| Euryarchaeota | phylum | 0 | 0 | 0 | 98.91 | 0.72 | 0.36 | 0 |
| Fusobacteriota | phylum | 0.72 | 0 | 0 | 98.19 | 1.09 | 0 | 0 |
| Verrucomicrobiota | phylum | 0.36 | 1.09 | 1.09 | 97.46 | 0 | 0 | 0 |
| Akkermansia muciniphila | species | 1.45 | 2.54 | 0.72 | 93.84 | 1.09 | 0.36 | 0 |
| Anaerotruncus colihominis | species | 1.81 | 0 | 0.36 | 96.01 | 1.09 | 0.72 | 0 |
| Bacteroides fragilis | species | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Bacteroides uniformis | species | 1.45 | 0.72 | 1.09 | 96.38 | 0.36 | 0 | 0 |
| Bifidobacterium longum | species | 1.45 | 0 | 1.09 | 97.46 | 0 | 0 | 0 |
| Butyrivibrio crossotus | species | 2.9 | 0.36 | 0 | 95.65 | 0.72 | 0.36 | 0 |
| Citrobacter freundii | species | 0.36 | 0 | 0 | 98.91 | 0 | 0.36 | 0.36 |
| Clostridioides difficile | species | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Collinsella aerofaciens | species | 1.45 | 0.36 | 0.36 | 96.74 | 0.72 | 0.36 | 0 |
| Coprococcus eutactus | species | 2.54 | 0 | 0 | 96.38 | 1.09 | 0 | 0 |
| Desulfovibrio piger | species | 2.9 | 0 | 0 | 95.65 | 1.45 | 0 | 0 |
| Enterobacter cloacae | species | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Enterococcus faecalis | species | 0 | 0 | 0 | 99.64 | 0 | 0.36 | 0 |
| Escherichia coli | species | 0.72 | 0 | 0 | 97.1 | 1.09 | 0.72 | 0.36 |
| Faecalibacterium prausnitzii | species | 0.36 | 0 | 1.81 | 97.46 | 0.36 | 0 | 0 |
| Helicobacter pylori | species | 0.36 | 0 | 0 | 99.64 | 0 | 0 | 0 |
| Klebsiella oxytoca | species | 0.36 | 0 | 0 | 98.91 | 0 | 0.36 | 0.36 |
| Klebsiella pneumoniae | species | 0.36 | 0 | 0 | 98.55 | 0.36 | 0.72 | 0 |
| Methanobrevibacter smithii | species | 2.54 | 0 | 0 | 95.29 | 1.09 | 0.36 | 0.72 |
| Oxalobacter formigenes | species | 2.17 | 0 | 0.36 | 96.38 | 0.72 | 0.36 | 0 |
| Phocaeicola vulgatus | species | 1.09 | 0 | 0.72 | 96.38 | 0.36 | 0.36 | 1.09 |
| Proteus vulgaris | species | 0 | 0 | 0 | 99.64 | 0.36 | 0 | 0 |
| Ruminococcus bromii | species | 2.54 | 0.36 | 0 | 96.01 | 1.09 | 0 | 0 |
BOOM
All suggestions are computed solely on their predicted microbiome impact. Safety, side-effects etc must be evaluated by your medical professionals before starting. Some items suggests have significant risk of adverse consequences for some people.
Special thanks to David F Morrison and Geert Van Houcke for doing Quality Assurance. Special thanks to Oliver Luk, B.Sc. (Biology) from BiomeSight for spot checking the coding of data from the US National Library of Medicine
This is an Academic site. It generates theoretical models of what may benefit a specific microbiome results.
Copyright 2016-2023 Lassesen Consulting, LLC [2007], DBA, Microbiome Prescription. All rights served.
Permission to data scrap or reverse engineer is explicitly denied to all users. U.S. Code Title 18 PART I CHAPTER 47 § 1030, CETS No.185, CFAA
Use of data on this site is prohibited except under written license. There is no charge for individual personal use. Use for any commercial applications or research requires a written license.
Caveat emptor: Analysis and suggestions are based on modelling (and thus infererence) based on studies. The data sources are usually given for those that wish to consider alternative inferences. theories and models.
Inventions/Methodologies on this site are Patent Pending.
Microbiome Prescription do not make any representations that data or analyses available on this site is suitable for human diagnostic purposes, for informing treatment decisions, or for any other purposes and accept no responsibility or liability whatsoever for such use.
This site is not Health Insurance Portability and Accountability Act of 1996 (HIPAA) compliant.
