Giotto Suite: A multi-scale and technology-agnostic spatial omics analysis framework

Giotto Suite: A multi-scale and technology-agnostic spatial omics analysis framework

Author(s): Jiaji George Chen,Joselyn Cristina Chavez-Fuentes,Matthew O'Brien,Irzam Sarfraz,Eddie Ruiz,Pratishtha Guckhool,Guo-Cheng Yuan,Ruben Dries

Affiliation(s): Boston University

Emerging spatial-omics technologies allow interrogation of the role of tissue architecture in specific biological processes, such as the establishment of cellular phenotypes or the inner workings of tissues. They can profile different molecular analytes such as chromatin accessibility, RNA, or protein, which represent different, but interconnected, layers of the cell regulatory network. Notably, with recent commercialization efforts and advancements in platforms that provide spatial imaging multiplex hybridization solutions, the range of spatial resolutions and information has widened significantly. From genome-wide information in coarse grained arrays down to the acquisition of individual transcript coordinates at subcellular resolution and unprecedented sensitivity. Together, these technologies offer complementary insights that lead to unparalleled opportunities to perform both discovery and validation research. However, integrating multiple modalities or operating with different spatial resolutions and levels of information, such as tissue or cell morphology, is currently a substantial challenge. Here, we present Giotto Suite, a comprehensive update and overhaul to our open-source R package Giotto that continues our emphasis on a completely technology agnostic framework that can represent virtually any type of spatial dataset and provide integrative solutions from raw data processing to visualization. Giotto Suite disentangles morphology, spatial and feature information to create a responsive and flexible framework to analyze spatial data at multiple scales. We are able to demonstrate the flexibility and use of this new framework on several state-of-the-art spatial technologies and show how multiple technologies on the same or adjacent slices of a tissue can be jointly represented to create a deep and comprehensive understanding of tissue function. Additionally, Giotto Suite aims to create an immersive ecosystem of spatial data analysis and tool development through the use of interoperability interfaces and data structures that overlap the established fields of genomics and spatial data science. Current compatibility functions include conversion from and to SpatialExperiment and SquidPy anndata, with others on the way. Project Website: Source Code:

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