  Motivation Modern molecular sequence analysis increasingly relies on
automated and robust software tools for interpretation, annotation, and
biological insight. The Analysis of Orthologous Collections (AOC) application
automates the identification of genomic sites and species/lineages influenced
by natural selection in coding sequence analysis. AOC quantifies different
types of selection: negative, diversifying or directional positive, or
differential selection between groups of branches. We include all steps
necessary to go from unaligned homologous sequences to complete results and
interactive visualizations that are designed to aid in the useful
interpretation and contextualization. Results We are motivated by a desire to
make evolutionary analyses as simple as possible, and to close the disparity in
the literature between genes which draw a significant amount of interest and
those that are largely overlooked and underexplored. We believe that such
underappreciated and understudied genetic datasets can hold rich biological
information and offer substantial insights into the diverse patterns and
processes of evolution, especially if domain experts are able to perform the
analyses themselves. Availability and implementation A Snakemake [M\"older et
al., 2021] application implementation is publicly available on GitHub at
https://github.com/aglucaci/AnalysisOfOrthologousCollections and is accompanied
by software documentation and a tutorial.
