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The engine behind human gut microbiome analysis and data science

As his career unfolds, biostatistician Kevin McGregor is becoming very familiar with the human gut microbiome. His work is particularly relevant given the human biome is a community of microorganisms that inhabit our bodies and appears to be linked to numerous health concerns, both physical and mental.

McGregor, an assistant professor in the Department of Mathematics and Statistics in the Faculty of Science, is a biostatistician who joined 快播视频 in 2021 after finishing his PhD at McGill University. He is part of the team involved in creating and teaching in the department鈥檚 , which makes its debut in 2023, but he is also involved in developing statistical models and associated software packages for understanding the makeup of the gut microbiome.

鈥淢y training is very quantitative, so I鈥檓 involved on the mathematical/statistical side,鈥 says McGregor. 鈥淭he microbiologists collect all the data and it鈥檚 my job to come up with the statistical methods to analyze it.鈥

Kevin McGregor
Kevin McGregor

He might be involved in looking into one species of microorganism if it鈥檚 abundant and considered relevant to a particular disease, such as Crohn鈥檚 disease, or he might be exploring the interaction between various types of microbes in the overall network.

鈥淢icroorganisms don鈥檛 live independently; they may be symbiotic or competing for resources,鈥 says McGregor. 鈥淲e鈥檙e looking for correlations related to metabolic interactions. I usually develop a methodology for analysis and the accompanying software. The first step is more theoretical; then, I create a software package so the microbiologists can plug in the data and get answers.鈥

Most of the studies compare the genetic sequencing for the microbiomes of hundreds of individuals. Researchers are looking at the counts of various species of microorganisms that are present to see if the patterns align with specific diseases or biomarkers.

One of the challenges of analyzing microbiome data is that numerous zeroes appear to indicate that certain organisms have no presence in an individual鈥檚 microbiome. Sometimes, these are false negatives; the stool sample that was used to sequence the individual鈥檚 gut microbiome simply didn鈥檛 include a specific microbe.

鈥淭hey are statistically difficult to deal with,鈥 McGregor says. 鈥淚t requires that I develop a statistical method that can look at the network patterns but get around this challenge.鈥

The programs that McGregor devises must determine what the probability is that any zero truly indicates the absence of that microbe. One of the methods he employs to weed out the false negatives is the zero-inflated logistic normal multinomial model.

Next comes the software development that allows him to 鈥渇it鈥 the model: input real data and get an output. Genetic sequencing of the microbiome provides 鈥渢ons of data,鈥 says McGregor, and the models are complicated. The associated software can take 鈥渉ours and hours to run鈥 on a computer, so he looks for shortcuts, such as the variational Bayes method, a statistical tool that is computationally efficient. McGregor is currently supervising a postdoctoral fellow, Isma茂la Ba, PhD, who is working on this model.

McGregor says he loves the problem-solving aspect of his work, devising new models or improving existing ones. He also likes the real-world applications that his work makes possible and enjoys the opportunity to collaborate with researchers in a broad range of fields. He recently joined forces with Joseph De Souza, an assistant professor of systems neuroscience, to apply for grants that will allow them to examine microbiome data related to Parkinson鈥檚 disease. He鈥檚 also involved with the Integrated Microbiome Platforms for Advancing Causation Testing and Translation (IMPACTT) team, which is a multi-disciplinary microbiome research core across Canadian universities.

鈥淢y dream is to be viewed as having a positive impact on microbiome research, developing models and giving sound advice to researchers in the field,鈥 McGregor says. 鈥淚鈥檇 also like to come up with statistically innovative techniques in this area and be recognized by the statistics community.鈥

McGregor鈥檚 career is young; look for its impact to grow exponentially.

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