Symptom – Bacteria Explorer Updated

As a side effect of starting a new blog on just the microbiome, , I am revisiting many of the pages that I have tossed up / evolved over the last 17 months.

This page is now updated to be easier to use as well as doing better statistics (well keeping things understandable). The initial page shows some random bacteria that is flagged at the 5% by chance level, but not truly significant (Eureka!). 5% of a thousand bacteria is 50!.

Clicking on one of the buttons will show the symptoms under a grouping and the number of people reporting this symptom. Clicking on one of these will add it to the filtering and recompute everything.

I clicked on No Health Issues to see there are common bacteria seen with those and not everyone else. We found one. Note that we change the color or the row.

The system automatically records these and they will be available on a new page in the future.

If you want to start a different path, just click the reset:

I went back and tried a different path, finding another bacteria. In this case we have 15+6+9 = 30, divide by 4 and we have 7 in each. So the result is that a shift towards lower values but no low values appears to be the association.

If you filter to less than 16 samples for this of symptoms, the page will inform you of this. Time to start over with a different path.

Some Real Results for IBS

As data is added, more things may appear

This is based on data to date, next on my list is making it easier to provide your symptoms. The link is there but many people are not seeing it.

The Math

This is by comparing this subset against the entire population by quantiles (all positive counts sorted and divided into quarters). If we have 64 readings, each of these quarters will have 64/4 = 16 readings. Looking at the filtered group, we look at how many falls into the same ranges of values and the perform a Chi2 computation to obtain significance.

For Eureka!~ we divide the number of bacteria we examined into 1 to get the PValue that would result in just ONE by random chance. We then divide this by 2 to raise the odds to just 50%.

To reduce the number of bacteria examined, we must have at least 16 non-zero readings. At the bottom of the page, we show how many bacteria and the Euraka PValue. In this case, it is 0.0014 and we found 0.000188 above, so we are almost 10x below this value and likely have found something.