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Spatial Experiments raster - a rasterization preprocessing framework for scalable spatial omics data analysis

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Spatial Experiments raster (SEraster)

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SEraster is a rasterization preprocessing framework that aggregates cellular information into spatial pixels to reduce resource requirements for spatial omics data analysis. This is the SEraster R documentation website. Questions, suggestions, or problems should be submitted as GitHub issues.

Overview

SEraster reduces the number of spatial points in spatial omics datasets for downstream analysis through a process of rasterization where single cells' gene expression or cell-type labels are aggregated into equally sized pixels based on a user-defined resolution. Here, we refer to a particular resolution of rasterization by the side length of the pixel such that finer resolution indicates smaller pixel size and coarser resolution indicates larger pixel size.

Installation

To install SEraster, we currently recommend using remotes:

require(remotes)
remotes::install_github('JEFworks-Lab/SEraster')

Tutorials

Introduction:

Citation

Our preprint describing SEraster is available on bioRxiv:

Aihara G. et al. (2024), "SEraster: a rasterization preprocessing framework for scalable spatial omics data analysis", bioRxiv

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