This is the released version of SEraster; for the devel version, see SEraster.
Rasterization Preprocessing Framework for Scalable Spatial Omics Data AnalysisBioconductor version: Release (3.21)
SEraster is a rasterization preprocessing framework that aggregates cellular information into spatial pixels to reduce resource requirements for spatial omics data analysis. SEraster reduces the number of spatial points in spatial omics datasets for downstream analysis through a process of rasterization where single cellsâ gene expression or cell-type labels are aggregated into equally sized pixels based on a user-defined resolution. SEraster is built on an R/Bioconductor S4 class called SpatialExperiment. SEraster can be incorporated with other packages to conduct downstream analyses for spatial omics datasets, such as detecting spatially variable genes.
Author: Gohta Aihara [aut, cre] ORCID: 0000-0002-2492-9610 , Mayling Chen [aut] ORCID: 0009-0009-0961-6665 , Lyla Atta [aut] ORCID: 0000-0002-6113-0082 , Jean Fan [aut, rev] ORCID: 0000-0002-0212-5451
Maintainer: Gohta Aihara <gohta.aihara at gmail.com>
Citation (from within R, entercitation("SEraster")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SEraster")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SEraster")Follow Installation instructions to use this package in your R session.
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