GUANIN can be installed with pip install GUANIN and it is available at https://pypi.org/project/guanin/. Source code, documentation, and case studies are available at https://github.com/julimontoto/guanin under the GPLv3 license.[Abstract]: Most tools for normalizing NanoString gene expression data, apart from the default NanoString nCounter software, are R packages that focus on technical normalization and lack configurable parameters. However, content normalization is the most sensitive, experiment-specific, and relevant step to preprocess NanoString data. Currently this step requires the use of multiple tools and a deep understanding of data management by the researcher. We present GUANIN, a comprehensive normalization tool that integrates both new and well-established methods, offering a wide variety of options to introduce, filter, choose, and evaluate reference genes for content normalization. GUANIN allows the introduction of genes from an endogenous subset as reference genes, addressing housekeeping-related selection problems. It performs a specific and straightforward normalization approach for each experiment, using a wide variety of parameters with suggested default values. GUANIN provides a large number of informative output files that enable the iterative refinement of the normalization process. In terms of normalization, GUANIN matches or outperforms other available methods. Importantly, it allows researchers to interact comprehensively with the data preprocessing step without programming knowledge, thanks to its easy-to-use Graphical User Interface (GUI).The supercomputer FinisTerrae III and its permanent data storage system have been funded by the Spanish Ministry of Science and Innovation, the Galician Government, and the European Regional Development Fund (ERDF). This study also received support by (i) ISCIII: TRINEO: PI22/00162; DIAVIR: DTS19/00049; Resvi-Omics: PI19/01039 (A.S.), ReSVinext: PI16/01569, Enterogen: PI19/01090 (F.M.-T.), cofinanciados FEDER, (ii) GAIN: IN607B 2020/08 and IN607A 2023/02 (A.S.), GEN-COVID: IN845D 2020/23 (F.M.-T.), IIN607A2021/05 (F.M.-T.); (iii) ACIS: BI-BACVIR (PRIS-3, to A.S.), CovidPhy (SA 304 C, to A.S.); and (iv) consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CB21/06/00103; to A.S. and F.M.-T.). In addition, this study has been funded by ISCIII through the project “CP23/00080” and co-funded by the European Union. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.Xunta de Galicia; IN607B 2020/08Xunta de Galicia; IN607A 2023/02Xunta de Galicia; IN845D 2020/23Xunta de Galicia; IIN607A2021/05Centro de Investigación Biomédica en Red de Enfermedades Respiratorias; CB21/06/0010
