Fall 2020: Investigating Microbial Communities
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Project presentations and podcasts.
BIT 477/577 Fall 2020 Students
Module Learning Objectives (MOs)
- MO 7.1. Compare different tools used for metagenomic analyses.
- MO 7.2. Apply tools we have covered (or new ones you have uncovered!).
- MO 7.3. Evaluate the best and most feasible approach for analyzing your sequences.
- MO 7.4. Apply tools from the course to analyze our datasets and address hypotheses.
I discovered that KBase Support is prompt and fantastic. I am also far less intimidated by Henry2. Here is a nice paper about the standards of certain metagenomic analysis practices to help with choosing in the future: https://www.nature.com/articles/s41598-018-30515-5
I learned about different tools used for metagenomic analyses, I’m particularly excited to spend more time with Kbase and Nephele and use them for my research. An article about Nephele: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905584/
One thing I discovered from this course, while it may be only tangentially related is that ASM has podcasts! https://asm.org/Podcasts/MTM/Episodes/Metagenomic-Sequencing-for-Infectious-Diseases-Dia
I learned how to use QIIME2 through Henry2 HPC. I am excited to try more tutorials on my own. You can find tutorials here: https://docs.qiime2.org/2020.11/
I learned a lot about analyzing metagenomic data using QIIME2 and the applications and meaning of the data generated. The main obstacle for me was learning the basic Linux commands and the command-line interface, which this site helped me with, particularly for the data analysis project, which was pretty satisfying when I got it right. https://maker.pro/linux/tutorial/basic-linux-commands-for-beginners
Some of the most exciting things learned in this course were about the free open-access bioinformatic programs available. Kbase is a broad platform that allows you to design your own pipeline. It has the ability to load multiple programs into the workflow by using the app feature. Nephele was user-friendly and only required the upload of the dataset and metadata and selection of a predesigned pipeline to start the analysis. Kbase provided an opportunity to learn more about each step in metagenomic analysis while Nephele was less cumbersome and more time-efficient.
In addition to learning the different platforms and pipelines, I learned a lot on how to troubleshoot and when it’s appropriate to contact support. I found the OIT support for Henry2 to be super nice and patient with my minimal understanding of HPC, while KBase support was a little more difficult to work with (the website itself was not cooperative and I found it annoying to have to go through another website to contact them). For Nephele, I found this resource helpful to understand the different facets and parameters, which helps prevent errors in the output.