Learning about the Human Microbiome

The following was written by Nur Majida Shahir, graduate student, Bioinformatics and Computational Biology at the University of North Carolina at Chapel Hill.

Mur Majida sitting in the lecture room

Nur Majida Shahir at the Microbiome workshop at SAMSI.

This past month, I had the opportunity to attend a workshop at the Statistical and Applied Mathematical Sciences Institute (SAMSI) on the human microbiome. While I was only able to attend the first day, the information and insight I gained over the course of the day was amazingly useful.

Dr. Susan Holmes gave the first talk of the morning session on Multi-Table Data Analysis. While the talk itself was interesting, the thing that stood out most to me was being introduced to an R package that was created by Dr. Holmes’ group called phyloseq. Prior to this workshop, the only downstream analysis program I knew of was Explicet but after being exposed to the flexibility of phyloseq, I have a feeling that I may be using the latter more in my research.

two people sitting by the SAMSI sign

Bill Shannon (L), Washington U. at St. Louis, and Timothy Randolph, (R) Fred Hutchison Cancer Center

Dr. Vanni Bucci gave the second talk of the morning on predictive modeling of microbiome dynamics. In contrast to the previous talk, this was approaching the microbiome from an applied mathematics perspective with a focus on creating and using a minimal model to study microbiota dynamics in enteric infections. I found this talk particularly fascinating in part due to my background in mathematics as well as the fact that looking at the microbial community dynamics in the gut makes sense due to the transient nature of some of the flora seen in the gut.

people sitting around a table

Nur participates in her first breakout working group session.

After the morning sessions and lunch, I had my first experience with a working group breakout meeting at this workshop. On one hand, it was a good experience to hear what people were thinking with regards to various datasets and the analysis of said dataset. There were many concepts and approaches that were thrown around that I honestly hadn’t thought of. On the other hand, I found it disorienting because I had a very superficial idea of what they were discussing. It would have been more beneficial if I had access to the data or at least the papers to which they were referencing prior to the working group breakout meeting.

One of the things that I enjoyed about this workshop was the varied backgrounds of the presenters. While the majority of the presentations were focused on statistics approaches and problems regarding the analysis of the microbiome, others approached the microbiome from a much more theoretical perspective as seen in Dr. Giseon Heo’s talk, which if I recall correctly, approached it from the perspective of knot theory.

four people in front of two posters

People discussing their work at the poster session.

The poster session was held at the end of the day. Reflective of the talks, the poster session content was fairly diverse content-wise as well with posters ranging from the “standard data analysis + results + future directions” to more methodology oriented approaches regarding how to approach the data. I personally enjoy poster sessions because they allow me to approach the material at my own pace and to interact with the presenter in a more direct manner.

All in all, I left the workshop very content. I’ve attended a few conferences where halfway through I’m utterly exhausted and dreading the next 4 hours. At this workshop, I felt that my time there was both well spent and informative.


Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s