The Best Microbiome Classes According To A Ph.D.
Updated: Feb 6, 2021
For those of you who don’t know I, Tess, the founder of Microbigals.com, have a Ph.D. in Genetics, Genomics, and Bioinformatics from the University of California Riverside. When I decided to pursue this degree, I was 22 years and old and had never opened a computer terminal, or even knew what a computer terminal was! When I decided to start Microbigals, I was 27 years old and had no web design or social media presence and when I decided to pursue a bachelor’s degree in Microbiology, I had no clue what microbes were. It just goes to show you that you never know where you are going to end up, and it’s usually small moments that define the rest of your life.
Now, grad school is no walk in the park. It’s typically 5 years of stress, depression, and frustration with a sprinkling of hope. Oh, and dark humor is also a must for grad school survival.
When you start your Ph.D. journey, everyone has a notion of what it’s going to be like, and that notion is always shattered. You are left with jagged shards of your reality. I now tell people grad school is 70% failing, 10% success, and 20% crying, but somehow it will be worth it in the end.
The three myths I had going into grad school was this (i) it's easy to bond with people and form friends because you all have a common love of science, (ii) the amount they (the school) grant you on your fellowship is the money you actually get without having to jump through any hoops, and (iii) you’re still a student and the people around you are there to help you. I had many other fallacies about grad school as I journeyed on my classic cross country road trip, but that’s for another post.
Today, I want to dive into the third of those myths, the part where I thought getting a Ph.D. in bioinformatics meant someone was actually going to teach me bioinformatics. Boy was that rude awakening! Needless to say, I’m a completely self-taught bioinformatician, spending the majority of my Ph.D. trying to figure out what Github was and using Stack OverFlow more than I ever used Google. I spent hours on a single error call and banged my head against my desk more than once out of frustration.
But through it all, I did build my own computer, was the bioinformatician and statistician for 5 peer-reviewed publications, and taught what I knew to some fellow grad students. I still struggle a lot with imposter syndrome and believing I have any bioinformatics skills worth a damn in the industry, but I’m also pleasantly surprised when I do get an error code today that I am much faster at finding a solution.
At any rate, I wanted to share with you the online resources that taught me everything I know about microbiome research, the resources that without, I never would have become a Ph.D. Here are my top 5 best resources for learning about microbiomes and how to analyze them.
Of the 5 resources, this is the best one for newbies. It does a great job of explaining what a microbiome is and uses giant microbes to help visualize concepts. It is taught by Dr. Rob Knight who is, in my humble opinion, a God of microbiome research (well I guess each person(s) who made it to this list I consider a God of modern-day microbiology). Dr. Jessica L. Metcalf and Dr. Katherine R. Amato also assist in teaching this course. Oh and many GiantMicrobes also help take the course so that's an automatic plus!
This is always the course I tell people to take when they are interested in learning about microbiome analysis. The course itself is over 5 years old now and was filmed back in Dr. Rob Knight was a faculty of the University of Colorado Boulder (he now teaches at UC San Diego). Despite its age and a fast-changing industry, I would still recommend this course.
The best part is you don’t have to be a scientist or have any fancy software in order to take this course! It really is designed for the absolute beginner, the person who is just microbe curious. If you don’t want to take my word for it, the course has over 71,458 people enrolled and counting with a 4.7-star review!
Ok, for real without this course I would not have passed my qualifying exam. For those of you who don’t know, a qualifying exam is like a right of passage for a Ph.D. student, pass it and you become a Ph.D. candidate, fail it and you could be kicked out. At my university, this was a 10 hour written exam over the course of 2 days followed by a 3-hour grilling section with your favorite (or not so favorite) faculty members.
I must have watched this 23 part Youtube series half a dozen times in preparation for my qualifying exam. I felt like I truly had a mentor in Dan Knights. This course covers both theory and application. If you want to get your hands dirty in a little bit of R coding this is your course. I would suggest, knowing a little bit of R before diving into this course though.
Dan Knights’ clear and concise teaching style accompanied by excellent visuals and hands-on tutorials really allow you to understand the microbial world from your computer. Fun fact: Dan Knights was also a Rubik’s cube master, so if you need a study break go check out his videos, they are only 30 seconds long after all!
Next up is Ben Callahan’s Dada2 tutorial. Dr. Ben Callahan is a professor at NC State University. This is a completely free tutorial I find myself going back to again and again. If you are looking for the theory behind microbiome analysis and what graphs are used in microbiome papers, this is not the place for you. This is the in-depth look of the Dada2 pipeline which is the backbone of a lot of microbiome analysis of today.
What is novel about this pipeline is its high resolution. Prior to DADA2, researchers clustered sequences that were highly similar into groups called operation taxonomic units or OTUs. With DADA2, it uses a machine-learning algorithm to look at the sequencing error rates that infer exact variants which they call ASVs or amplicon sequence variants. This means similar sequences are not clustered together, only sequences that are exact (or just 1 nucleotide off). The other thing that is great about this pipeline is that it is entirely in R. When I was learning, I struggled so much with the wrapper scripts because I didn’t understand what was happening. In comes DADA2, and finally, I’m able to easily see what is going on and what it is doing to the data in a language I understood (or at least was learning). I didn’t have to switch between platforms or languages for my whole analysis; it was all in one place.
This tutorial walks you through the steps from receiving your sequences, filtering for quality, building your sequence table to basic visualizations of the data. It’s a hodgepodge of code, text, and cautions that thoroughly walk you through the first steps of microbiome analysis whether you are using his provided data or your own.
This is my recent obsession. There are two types of microbiome analysis. What we call amplicon metagenomics and full metagenomics. Up until now, we’ve been talking about amplicon sequencing. In this approach, you sequence just an itsy-bitsy portion of the full genome and hundreds (or thousands) of microbes. With this tiny piece of DNA, researchers are able to identify, with fairly good certainty, who the microbe is, but you lack what the microbiome can do; this is where full metagenomics comes in. Here, you sequence the full genomes of hundreds (or thousands) of microbes and try to identify not only who they are but what they are capable of doing.
The Meren lab has developed a pipeline called Anvi’o which is an open-source and community-driven analysis for full metagenomics. Again, this is not one for beginners, but for people who want to do a deep dive into metagenomics research. The tutorials are not only informative but are also funny and the visualizations are pure art. If you’ve never looked at data and said “wow that’s beautiful” go look at these graphs.
The Meren lab also puts together some phenomenal webinars. When watching them you really feel like Meren cares about not only his research but about providing high quality and free resources, putting the analysis in the hands of whoever is willing to learn it. I recently took a 6 part webinar series with the Meren Lab and by the end, I not only improved my science communication, visualizations, and analysis skills, I truly felt like I was a part of something bigger and beautiful.
This is another MOOC like number one on our list, “Gut Check” but this one is on edX as opposed to Coursera. The course is free but like many MOOCs, you can pay a small fee to get a certificate of completion. This course is the brainchild of Karoline Faust and Lisa Rottjers at KU Leuven in Belgium. The course is broken down into 6 modules of learning and a final exam module. This is another one meant for people at more of an intermediate level but is chock-full of vital information for any undergraduate/graduate student embarking on a microbiome journey.
What you’ll learn? Well, they lay all out for you in the title. This is a pretty comprehensive course to learn how to analyze a microbiome both theory and in practice. They go over everything from sequencing to analyzing to how to interpret graphs. It’s truly an incredible resource with some brilliant visuals. What makes this course stand out among the rest is the graphics. They are amazing! I definitely give props to whoever developed their animation for the videos. If you are a visual learner this one is a must!
So there you have it! That is basically all my secrets to getting a Ph.D. Well, that and Ph.D. stands for perseverance, hard work, and determination. A Ph.D. is not for the intelligent, and if you saw a grad student pay stub you know it's not for the rich. A Ph.D. is for the curious, the courageous, and above all else the resilient. So if you are in a similar boat that I was, needing to learn microbiome, with little guidance as quickly as possible, with little to no programming experience, I hope you find these resources helpful. If on the other hand, you were in a similar boat as I was, not knowing how to do what you need to do, I hope this gives you a little inspiration or at least motivation to continue searching for what you need. And if you find yourself in neither of these boats, I ask you, are you even human?
Have you found mentors and knowledge in unexpected places before? Tell us in a comment below!