The R package boost (Bayesian Modeling of Spatial Transcriptomics Data) provides functions to detect spatially variable (SV) genes in spatial transcriptomics (ST) data. This package provides two novel Bayesian methods, as well as other standard procedures, for facilitating studies in spatial molecular profiling (SMP). For the step-by-step tutorial of boost, please refer to https://boost-r.readthedocs.io/en/latest/
The latest version of the package is under development at GitHub, which can be installed from GitHub by:
devtools::install_github("estfernan/boost")
library(boost)SPARK is a dependency and is necessary for using the SPARK model.
It can be installed from GitHub by:
devtools::install_github('xzhoulab/SPARK')SpatialDE is also necessary for using the SpatialDE model.
It can be installed from Bioconductor by:
BiocManager::install('spatialDE')-
Jiang, X., Li, Q., & Xiao, G. (2021). Bayesian Modeling of Spatial Transcriptomics Data via a Modified Ising Model. arXiv preprint arXiv:2104.13957.
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Li, Q., Zhang, M., Xie, Y., & Xiao, G. (2020). Bayesian Modeling of Spatial Molecular Profiling Data via Gaussian Process. arXiv preprint arXiv:2012.03326.