RERconverge Update: Runtime Reduction and Analysis Function Overhaul
Guillermo L. Hoffmann, Emily E. K. KopaniaiD, Michael TeneiD, Amanda Kowalczyk, Ruby W. RedlichiD, Andreas R. PfenningiD, Wynn K. MeyeriD, Maria D. ChikinaiD, Nathan L ClarkiD
Abstract
MotivationConvergent evolution, or the independent acquisition of similar phenotypes in distinct lineages, provides a powerful framework for investigating genomic changes associated with a phenotype. This paper details an update to RERconverge, a powerful R package that tests for associations between gene relative evolutionary rates (RERs) and convergent phenotypes to infer genomic regions associated with traits or selective pressures. We introduce new customizable analysis choices and scalable and efficient algorithms that can process larger genomic datasets, a critical improvement as genomic data become available for more species. ResultsModifications to core functions in the RERconverge pipeline resulted in an immense speedup (by a factor of up to 28.6). The function that tests for associations between phenotypes and RERs has been expanded to include two new analytical methods for outlier control; we also provide here a summary of the statistical tests users can perform, along with their use cases. Availability and implementationThe code and walkthrough vignettes for the package are available at https://github.com/nclark-lab/RERconverge. ContactNathan L. Clark nclark@pitt.edu; Maria Chikina mchikina@pitt.edu
02 /Specification & Classification
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