Esposito, Salvatore https://orcid.org/0000-0002-2785-1468
Scalzi, Nicola
Palombieri, Samuela
Sanseverino, Walter
Sestili, Francesco
Stella, Alessandra
Balestrini, Raffaella
Grillo, Stefania
Bressan, Ray Anthony
Batelli, Giorgia https://orcid.org/0000-0003-1554-218X
Funding for this research was provided by:
Consiglio Nazionale Delle Ricerche
Article History
Received: 15 June 2026
Accepted: 14 August 2026
First Online: 29 August 2026
Declarations
: Project name : SNPoptimizer.
: Project home page : .
: Operating system(s) : Platform independent.
: Programming language : R (version ≥ 4.2).
: Other requirements : R packages: shiny (Chang et al. ), GA (Scrucca ; ), data.table (Barrett et al. ), tidyverse (Wickham et al. ), DT (Xie et al. ), ggplot2 (Wickham ), plotly (Sievert ), shinyWidgets (Perrier et al. ), BiocManager (Morgan et al. ), Biostrings (Pagès et al. ), parallel (Corporation et al. ), shinycssloaders (Attali et al. ).
: Browser : Any web browser (Chrome, Firefox, Safari, Edge).
: License : GPL-3.
: Any restrictions to use by non-academics : No restrictions for GPL-3 (commercial use allowed under license terms).
Generative AI and AI-assisted technologies: During the preparation of this work, the authors used two generative-AI tools: Codex 5.3-codex (OpenAI; accessed up to January 2026) and ChatGPT (OpenAI, GPT5.5; accessed up to March 2026). These tools assisted with (i) revising and debugging Python scripts ii) improving the text to improve clarity and readability. All AI-generated suggestions were critically reviewed and edited by the authors. The authors take full responsibility for the integrity and accuracy of all content presented in this manuscript.
Competing interests: The authors declare no competing interests.