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nnSVG

Bioc current

Scalable identification of spatially variable genes in spatially-resolved transcriptomics data

v1.16.0 · software · MIT + file LICENSE
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Release Lineage

Entered 3.15 · Apr 27, 2022

Current · Requires R 4.6

1.0 In 9 of 49 releases 3.23

Description

Method for scalable identification of spatially variable genes (SVGs) in spatially-resolved transcriptomics data. The method is based on nearest-neighbor Gaussian processes and uses the BRISC algorithm for model fitting and parameter estimation. Allows identification and ranking of SVGs with flexible length scales across a tissue slide or within spatial domains defined by covariates. Scales linearly with the number of spatial locations and can be applied to datasets containing thousands or more spatial locations.

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Topics

Software › Technology › Spatial
Software › Technology › SingleCell
Software › ResearchField › Transcriptomics
Software › AssayDomain › GeneExpression
Software › WorkflowStep › Preprocessing

Depended on by (4)

Bioconductor (4)

SEraster spoon tpSVG OSTA

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