SSAM-lite: A Light-Weight Web App for Rapid Analysis of Spatially Resolved Transcriptomics Data.

Autor:	Tiesmeyer S; Digital Health Center, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany., Sahay S; Digital Health Center, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany., Müller-Bötticher N; Digital Health Center, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany., Eils R; Digital Health Center, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany.; Health Data Science Unit, Heidelberg University Hospital, Heidelberg, Germany., Mackowiak SD; Digital Health Center, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany., Ishaque N; Digital Health Center, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany.
Jazyk:	angličtina
Zdroj:	Frontiers in genetics [Front Genet] 2022 Feb 28; Vol. 13, pp. 785877. Date of Electronic Publication: 2022 Feb 28 (Print Publication: 2022).
DOI:	10.3389/fgene.2022.785877
Abstrakt:	The combination of a cell's transcriptional profile and location defines its function in a spatial context. Spatially resolved transcriptomics (SRT) has emerged as the assay of choice for characterizing cells in situ . SRT methods can resolve gene expression up to single-molecule resolution. A particular computational problem with single-molecule SRT methods is the correct aggregation of mRNA molecules into cells. Traditionally, aggregating mRNA molecules into cell-based features begins with the identification of cells via segmentation of the nucleus or the cell membrane. However, recently a number of cell-segmentation-free approaches have emerged. While these methods have been demonstrated to be more performant than segmentation-based approaches, they are still not easily accessible since they require specialized knowledge of programming languages and access to large computational resources. Here we present SSAM-lite, a tool that provides an easy-to-use graphical interface to perform rapid and segmentation-free cell-typing of SRT data in a web browser. SSAM-lite runs locally and does not require computational experts or specialized hardware. Analysis of a tissue slice of the mouse somatosensory cortex took less than a minute on a laptop with modest hardware. Parameters can interactively be optimized on small portions of the data before the entire tissue image is analyzed. A server version of SSAM-lite can be run completely offline using local infrastructure. Overall, SSAM-lite is portable, lightweight, and easy to use, thus enabling a broad audience to investigate and analyze single-molecule SRT data. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Tiesmeyer, Sahay, Müller-Bötticher, Eils, Mackowiak and Ishaque.)
Databáze:	MEDLINE
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