SSAM-lite: a light-weight web app for rapid analysis of spatially resolved transcriptomics data

<jats:label>1</jats:label>Abstract 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.Availability and Implementation SSAM-lite is an open-source browser-based web application with source code freely available on Github via <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/HiDiHlabs/ssam-lite">https://github.com/HiDiHlabs/ssam-lite</jats:ext-link>. Stable releases can be accessed via <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://ssam-lite.bihealth.org">https://ssam-lite.bihealth.org</jats:ext-link> and <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://ssam-lite.netlify.app">https://ssam-lite.netlify.app</jats:ext-link>, and developmental releases can be accessed via <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://dev--ssam-lite.netlify.app">https://dev--ssam-lite.netlify.app</jats:ext-link>. The source code for a locally deployable server version, SSAM-lite-server, is available on GitHub via <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/HiDiHlabs/ssam-lite-server">https://github.com/HiDiHlabs/ssam-lite-server</jats:ext-link>. Both versions require a modern browser with JavaScript and WebGL support. Detailed user guides and documentation can be found at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://ssam-lite.readthedocs.io">https://ssam-lite.readthedocs.io</jats:ext-link>..

Medienart:	Preprint

Erscheinungsjahr:	2022
Erschienen:	2022

Enthalten in:	bioRxiv.org - (2022) vom: 25. Mai Zur Gesamtaufnahme - year:2022

Sprache:	Englisch

Beteiligte Personen:	Tiesmeyer, Sebastian [VerfasserIn] Sahay, Shashwat [VerfasserIn] Müller-Bötticher, Niklas [VerfasserIn] Eils, Roland [VerfasserIn] Mackowiak, Sebastian D. [VerfasserIn] Ishaque, Naveed [VerfasserIn]

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doi:	10.1101/2021.09.29.462194

funding:
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PPN (Katalog-ID):	XBI032702213