Combinatorial selections experiments are useful experimental tools to identify biopolymers with specific biological, biomedical, or chemical characteristics. Aptamers – one class of these biopolymers – are short, single-stranded nucleic acids that are typically generated via an iterative scheme termed SELEX in which high- and low-fitness aptamers respectively enrich or deplete over the course of the selection, which can have up to millions of unique sequences. While there any many post-SELEX analytical tools built for high-throughput sequencing data, they typically have a high entry barrier for new users because they require significant computational expertise to operate. Our recently published tool – FASTAptameR 2.0 – minimizes this barrier-to-entry while still maintaining the ability to answer complex sequence-level and population-level questions. While this open-source toolkit features many significant upgrades to its first version (e.g., user interface, interactive graphics and data analytics, etc.), the most recent version of the tool features many new, unpublished modifications. First, the backend of FASTAptameR is optimized 1) to more efficiently process user data and 2) to allow asynchronous data processing on its web server. Second, FASTAptameR is now available as a standalone R package, allowing users to process their data in bulk. Third, this tool now features many new analytical modules that allow users to preprocess sequence data, perform differential analyses, and more. Altogether, these upgrades further enhance the user experience and support more diverse experimental designs.
