Statistically significant bacteria for Immune Manifestations: medication sensitivities. using biomesight lab pipeline and genus taxonomy

This page has been revised to make visually clear the shifts and significance to non-statisticians. Statisticians are welcomed to download the full data and process it themselves.

Shift - the direction that the top and bottom 16% is expected to change. Note that the mean, median and other standard statistical method may not alter significantly
If there was independence - then the number below 16%ile and above 84%ile should be almost the same. Percentile is a uniform distribution and not a gaussian distribution
Prevalence - How often this taxa is identified by this lab pipeline
Chi2 with one degree of freedom - we evaluate two chi2 and report the highest only

Using this information have found significantly accurate prediction of symptoms on new people using the same pipeline. The same FASTQ file processed thru ubiome, Ombre, Biomesight and sequentia biotech; resulted in different genus being reported with different amounts. Clearly, the associations is processing pipeline dependent.

This table is regenerated every month on the 2nd using the latest data
Bacteria	Shift	Prevalence	Number below 16%ile	Number above 84%ile	Chi2
Haemophilus	increases	75.24	11.0	15.0	7.93
Porphyromonas	decrease	82.75	18.0	11.0	10.14
Alkaliphilus	decrease	97.78	22.0	2.0	12.94
Limnobacter	increases	72.44	3.0	15.0	10.86
Anaerostipes	decrease	89.12	18.0	3.0	9.12
Hydrocarboniphaga	increases	74.87	4.0	16.0	9.56
Desulfurispora	decrease	54.38	14.0	4.0	10.32
Negativicoccus	increases	53.13	3.0	14.0	9.02
Hathewaya	increases	98.52	7.0	17.0	7.21
Schaalia	decrease	49.16	13.0	1.0	7.32

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