Turning qualitative observation to quantitative measurement through statistical computing: vignettes from microbiology and genetics
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Description
Biological studies seek to derive explanation for the patterns we see in the world around us. Although qualitative observations are helpful to identify potentially interesting phenomena, unbiased numerical quantification is required for hypothesis testing. Here I will describe how we turn qualitative into quantitative though computational statistical analyses. Drug tolerance, the ability of a subpopulation of microbial cells to grow above the drug resistance level, had previously been noted but largely ignored in clinical assays. We developed the R package diskImageR to parameterize photographs of disk diffusion assays, a common clinical assay used to measure drug resistance. Through quantification of drug tolerance, evidence is now mounting that tolerance may influence the likelihood of evolving resistance as well as the propensity for recurrent infections. A second R package, dgconstraint, was developed to quantify observations of convergent adaptation. Convergent adaptation occurs at the genome level when independently evolving lineages use the same genes to respond to similar selection pressures. We formulated a novel index to quantify the constraints driving the observed amount of convergent adaptation in pairwise contrasts based on the hypergeometric distribution. We then applied the index to measure the amount of convergence observed in whole genome sequencing datasets from microbial experimental evolution studies to test a range of hypotheses about the factors that facilitate or constrain the diversity of genetic responses observed during adaptive evolution.
About Aleeza Gerstein
Aleeza did her undergraduate degree in Ecology & Evolution at the University of Western Ontario (now inexplicably Western University) where she studied things like Desert Ecology and Meadow Sparrows. She then moved to the University of British Columbia for her MSc. and Ph.D., where she became enamoured with coding in R, evolving microbes in test tubes, and the ability to pinpoint specific mutations through whole genome sequencing and bioinformatic analyses. She conducted her postdoctoral work with human fungal pathogens at Tel Aviv University and The University of Minnesota, where she continued to expand her appreciation for how statistical computing could open up the world of biological questions that can be addressed. Finally she migrated back home to Winnipeg, where she now holds a joint appointment between the departments of Microbiology and Statistics at the University of Manitoba.