Resources

More data means more analysis! Large datasets containing swathes of clinical and biological information have become more common in the last decade. Still, integration and mining of complex data remains difficult to navigate for a large portion of researchers with limited bioinformatic skills. We thus developed ‘Hourglass’, an open-access analytical framework that streamlines biology-driven visualization, interrogation, and statistical assessment of multiparametric bioimaging datasets. Cognizant of tissue and clinical heterogeneity, Hourglass systematically organizes observations across spatial and global levels and within patient subgroups. This facilitates knowledge extraction from multi-layered bioimaging datasets for users with or without computational proficiency and provides unique and widely accessible analytical means to harness insights hidden within heterogeneous tissues at the sample and patient level.

Hourglass is available as a stand-alone R package with an optional user-friendly desktop application (detailed user’s guide and test dataset at https://kazeera.github.io/Hourglass).