What Do Your Results Mean? Go In Depth With A uBiome Data Scientist.

Some of you might be wondering…

What do my results mean?
What can I learn from this test?
What is a firmicutes, anyway?

At long last, here’s your chance to find out.

Book your exclusive 20-minute Skype or phone session with one of our data scientists here at uBiome to help you understand the specifics of your microbiome test results.

For example, you could be talking one-on-one with:

We look forward to answering your questions and helping to make meaning from your data! We’re offering this for a limited time at $149.

Schedule your spot now at http://ubiome.com/products/data-help


All my uBiome results in a single table

Here’s another wonderful post by our great friend Richard Sprague. Thanks Richard!

I often read news about a fresh scientific discovery involving the microbiome and immediately wonder if the discovery applies to me.

For example, I recently saw a study from Oregon State University that seemed to find a link between high sugar diets and “cognitive flexibility”, i.e. your ability to adapt and adjust to changing circumstances. The study’s author, Kathy Magnusson, a professor in the OSU College of Veterinary Medicine, found that mice who eat lots of sugar have elevated levels of Clostridiales bacteria, and that this seemed to relate to a slower ability to solve a maze.

Hmmm, I thought — how much Clostridiales do I have?

If you have just one uBiome result, that’s easy: log into http://app.ubiome.com and search for it in the section “All My Bacteria”. (As far as I know there’s no “search” button yet on the uBiome dashboard). But in my experience a single result doesn’t tell you much. You really need at least two and hopefully several uBiome results to see what might be actionable.

In my case, I want to know how my Clostridiales may have changed over time.

I programmed a short Python script to generate a single Excel table with every bacteria I’ve ever found, and then a series of columns with the amount found in each sample. Something like this:


The data makes it easy to generate a chart showing how my Clostridiales changes over time:


Hmmm, in my case it looks like something happened since last fall to increase my Clostridiales levels. Maybe it was the potato starch I tried in order to hack my sleep? Was it my trip to Central America in February? And of course the biggest question: has the increase affected my cognitive flexibility? I’m not really sure. Whatever happened, the level of Clostridiales seems to have stabilized in the past couple of months.

uBiome has identified more than 900 unique taxa (groups of organisms) in the half-dozen samples I’ve submitted over the past year, and after running this script I have them all laid out on a single page.

Armed with this one spreadsheet I can search anytime for a new microbe and quickly see if I have it now, or if it’s ever been detected in a previous test. Reading news about the microbiome takes on a whole new personal meaning when I can see if the discovery relates to me.

(If you know a little Python, you can make the same spreadsheet with your samples using the ubiome.py Python module on the ubiome-opensource GitHub repository; the script that generated my spreadsheet is there too as an example. Happy exploring!)

New open source uBiome github repository for data analysis tools

uBiome was founded to help all citizens contribute to science. Many uBiome users have been asking if we can make it easier for them to analyze their own data, and now we’re pleased to announce a new Github site to let you do exactly that.

The site has a repository called microbiome-tools (for sharing tools, templates, scripts, or other software or utilities you find useful for analyzing your uBiome data).

To contribute, all you need is a (free) Github account from which you can send pull requests. If you’re brand new to Git or Github and you want to learn more, check out this beginners guide: http://readwrite.com/2013/09/30/understanding-github-a-journey-for-beginners-part-1

Please note that everything in these repositories is being made available under the Creative Commons International license, and by uploading your tools you are agreeing that you own the information and that you agree to share them with everyone.

Share away! Let’s all learn together.

That link again is: https://github.com/ubiome-opensource

Your friends, Alexandra Carmichael (@accarmichael) and Richard Sprague (@sprague)

Announcing The New uBiome Data Website

I think you’ll be excited to see this. If you’re new to uBiome, or already have 50 samples under your belt, we have some great news for you. The microbiome timeline has arrived. 

The new uBiome site officially launches today at http://app.ubiome.com. Now it’s easy to see all your samples in one place, and find out how your microbiome is changing over time.

When you log in, you’ll see something like this.

Screen Shot 2015-05-11 at 1.00.53 PM


You can drill down deep into each sample shown in the timeline graph. Find out how you compare to all the samples in the uBiome community, or just to specific groups like women or men, vegans or paleo enthusiasts, and people with acne or yeast infections.

You’ll see how you’re different. And explore what that might mean.


Screen Shot 2015-05-11 at 1.03.57 PM


At the bottom of the dashboard, you can download your raw sample data and explore your bacterial tree. We’ve also thrown in a few fun things to read that will always be fresh for you each time you come. At the very bottom are links to the uBiome community around the web, for you to connect with if you so choose.


Screen Shot 2015-05-11 at 1.06.14 PM


When you’re taking your samples, the My Samples page will both give you instructions and let you know the status of your precious microbial specimens. We’ll get them back to you just as soon as we can.


Screen Shot 2015-05-11 at 1.30.57 PM


For each sample, there is a set of survey questions to help connect your current state of health and lifestyle choices with the state of your microbiome. It’s like a snapshot in time. The more questions you answer, the easier it will be to make correlations and even new discoveries about human health as it relates to our bacterial friends.


Screen Shot 2015-05-11 at 1.31.20 PM


That concludes our brief tour of the new site. Please check it out for yourself at http://app.ubiome.com. And definitely let us know what you think! We always strive to improve and help you gain new insights.

Here’s to your microbiome!



A Surprising Comparison of Male vs. Female Microbiomes

I must admit, I was curious. So I went over to the desk of our brilliant Lead Data Scientist, Dr. Siavosh Rezvan-Behbahani, to find out.

Could you look at all of uBiome’s gut samples, I asked, and see what the difference in microbiome composition is between men and women? And the corollary, is it possible to predict from microbiomial data whether the person giving the sample was male or female?

With human DNA, of course you can determine gender based on the chromosome signature XX vs. XY. But does the microbiome have a gender signature too?

Siavosh dove in. He spent many hours analyzing, plotting numbers, running different machine learning classifier algorithms. He looked at healthy male and female samples in part of our dataset, all the way down to genus level.

And here’s what he found, which blew my mind.

male female ubiome

It turns out that in our dataset, there is no statistically significant difference between male microbiomes and female microbiomes. And, given a random sample, we would not be able to determine if it came from a man or a woman.

This result is fascinating to me, because it suggests that maybe men and women aren’t that different in some ways. We all have two eyes, and belly buttons, and similar proportions of bacteria swimming around inside our intestines.

(Of course there’s the standard disclaimer that this is just what we observe in our gut dataset, and may not be representative of the entire human population. It’s also possible that there is a difference but it’s much more subtle than we expect. In any case, this result is encouraging me to think up other questions to ask!)

If you’re curious about something too, please tell me in the comments what kinds of data discoveries you’d like to hear about next.