Sample Comparison Tools

This set of tools is designed for two scenarios:

  • One person who has had many samples of time. Typically that person is looking for outliers to reduce or disappear
  • A family with samples from different members. Typically one person is challenged and since the family group has shared DNA and diet — the hope is that the bacteria grouping causing the challenge will be identified. Once identified, it may be actionable.
    • This scenario will have more tools added over the next weeks.

I have used them in these prior posts:

If you have two or more samples uploaded, you will see the top two items on the Available Samples page. These may be collapsed into one over the next few weeks.

Clicking the right button of these two will take you to a sample selection page.

Clicks TWO or more samples

The program will list all items below that matches all samples OR all samples except 1 (but at least two).

I selected a group of 5 samples from when I was having a ME/CFS flare.

The lack of dehydrogenases above would account for high lactate(brain fog) and agrees with research [Nicotinamide adenine dinucleotide (NADH) in patients with chronic fatigue syndrome]

IMHO, it correctly identified what was wrong with me.

KEGG Modules takes a bit of research to understand.

Doing some research, I found “. L-tryptophan is produced in the shikimate pathway from chorismate” Which lead to many ME/CFS articles on PubMed.

Again, it may take some research to understand what this is.

This informed me which bacteria were constantly high over 5 samples

The cause of ME/CFS flare was stress and a quick search on PubMed found several articles where this genus increased with stress, the latest was “Gut Microbiota Are Associated With Psychological Stress-Induced Defections in Intestinal and Blood–Brain Barriers“[2020]

Bottom Line

This set of tools does not give immediate answers; it gives you leads to investigate. For myself, the findings plus the use of PubMed studies weaved a story of what happened that agrees with the literature. This is very important because ME/CFS contains dozens of subsets. Often I have seen that what is helpful for one subset is harmful for another. I suspect this also applies to other conditions, such as ASD/Autism.

In this case, it identified one key family to reduce. Identified enzymes that I was short on. Lead to a possible supplements that I should consider because of the dysruption.

One thought on “Sample Comparison Tools

  1. In terms of the advantages of HULK over other de novo analysis methods (e.g. k-mer spectra dissimilarity analysis), we have shown here that the computation of histogram sketches from complete metagenomic datasets is 16 times faster than the computation of the full k-mer spectra and 17 times faster than the computation of the MinHash sketch (see the “ Clustering microbiome datasets ” section and Fig. 2 ). In terms of performing sketching faster than sourmash’s compute function, we should stress that the better performance seen by HULK is due to the ability to parallelise the histosketching process (both tools run in a similar time on a single core). All tools produced a fairly accurate clustering of the microbiome samples, according to the body site from which the microbiomes were designed to originate, with HULK actually producing the most accurate clustering in this sense. We suggest that the incorporation of k-mer frequency information into the sketch generation may account for the better clustering performance of HULK compared to that of sourmash, which differs by using k-mer abundance for weighting the distance calculations and not the sketch generation. As well as faster analysis times, histogram sketching has a much smaller footprint as the entire k-mer spectrum does not need to be kept in memory or written to disk, and the resulting sketches are much smaller in size than the full spectrum. As with other sketching methods, HULK also does not require re-computation of previously sketched samples in order to make new comparisons (provided new samples are sketched using the same parameters).

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