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README.md

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 ARETE produces a range of useful outputs, including those generated by each tool integrated into the pipeline, as well as summaries across the entire dataset such as phylogenetic profiles. Outputs from ARETE can also be fed into packages such as Coeus and MicroReact. Although ARETE was primarily developed with pathogens in mind, inference of pan-genomes, mobilomes, and phylogenomic histories can be performed for any set of microbial genomes, with the proviso that reference databases are much more complete for some groups than others! The tools in ARETE work best at the species and genus level of relatedness.
 
-A key design principle of ARETE is finding the right choice of software packages and parameter settings to support datasets of different sizes, introducing heuristics and swapping out tools as necessary. ARETE has been benchmarked on datasets ranging in size from fewer than ten to over 10,000 genomes from a multitude of species and genera including _Enterococcus faecium_, _Escherichia coli_, _Listeria_, and _Salmonella_.
+A key design principle of ARETE is finding the right choice of software packages and parameter settings to support datasets of different sizes, introducing heuristics and swapping out tools as necessary. ARETE has been benchmarked on datasets ranging in size from fewer than ten to over 10,000 genomes from a multitude of species and genera including _Enterococcus faecium_, _Escherichia coli_, _Listeria_, and _Salmonella_. Another key principle is letting the user choose which subsets of the pipeline they wish to run; you may already have assembled genomes, or you may not care about, say, recombination detection. There are also cases where it is useful to manually review the outputs from a particular step before moving on to the next one. ARETE makes this easy to do. 
 
 # Table of Contents
 1. [About the pipeline](#about)