Spatial Random Effects Clustering of Single Cell Data
Overview
Allows for identification of cell sub-populations within tissue samples using Bayesian multivariate mixture models with spatial random effects to account for a wide range of spatial gene expression patterns, as described in Allen et. al, 2021 doi:10.1101/2021.06.23.449615. Bayesian inference is conducted using efficient Gibbs sampling implemented using 'Rcpp'.
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- 24includes a package overview page
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- 11%2 run in a plain check · 16 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
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People & History
- RR 4.3.0 released · 2023-04-21
- archivedRemoved from CRAN2022-12-05issues were not corrected despite reminders
- RR 4.2.0 released · 2022-04-22
- 0.99.12022-02-21
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-02-21
- Total releases
- 1 / 4 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.0
- Bundled data
- 5.8 KB / 1 file
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