pySuStaIn: A Python implementation of the Subtype and Stage Inference algorithm

• Published in: SoftwareX Vol. 16; p. 100811
• Main Authors: Aksman, Leon M., Wijeratne, Peter A., Oxtoby, Neil P., Eshaghi, Arman, Shand, Cameron, Altmann, Andre, Alexander, Daniel C., Young, Alexandra L.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2021; Elsevier
• Subjects: Disease heterogeneity; Disease progression modeling; Disease staging; Disease subtyping; Disease progression modeling; Disease heterogeneity; Disease subtyping; Disease staging; disease heterogeneity; disease subtyping; disease staging
• ISSN: 2352-7110; 2352-7110
• DOI: 10.1016/j.softx.2021.100811

Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modeling situations within a single, consistent architecture.