Making pipelines and large processing microbial community studies available to any user, any time, any place
- Author(s): Navas Molina, Jose Antonio
- Advisor(s): Knight, Rob
- et al.
Advances in ’omics technologies are producing vast amounts of data, bring- ing microbiome research to a whole new level. This increase in data is pushing the limits of existing analysis tools, creating a rapidly-changing environment in which new tools are constantly being released. This presents a challenge to researchers, who need to constantly learn new analytical tools, expose themselves to new envi- ronments such as cloud computing or supercomputers, and deal with the problems resulting from a heterogeneous environment lacking the enforcement of standards. This thesis demonstrates how computational optimizations, enforcement of stan- dards, and minimizing the learning curve for analytical tools and computational environments empower researchers to push the microbiome field forward.
Chapter 1 motivates and contextualizes the thesis, exposing the challenges and opportunities that current microbiome research faces as it presents itself as a big data field. Next, Chapter 2 presents the first gold standard approach for an- alyzing microbiome data, improvements in analytical tools, and examples of how these improvements move microbiome research forward. Chapter 3 describes a system that lowers the access barrier to cloud computing that researchers without a computational background face. Chapter 4 exposes the importance of meta- analyses to increase researchers’ ability to discover new findings and how much effort is currently spent to perform such meta-analyses. This chapter also presents Qiita, a web-based system focused on facilitating meta-analyses by enforcing stan- dards, normalizing data representation and processing, and providing a common interface to current state-of-the-art analysis tools. Chapter 5 describes how using the tool improvements and data standardizations presented in Chapters 2 and 4, respectively, and a novel system that aids the recording of sample handling in- formation, speed up the process of analyzing microbiome samples to levels never reached before. Finally, the concluding chapter of this thesis discusses the results and the opportunities opened due to these advances, paying special attention to precision medicine, a topic in which the microbiome is becoming key.