31-Mar-2022: espresso 1.0.1 released.
espresso is a package for domain estimation of cells only from gene expression profile based on graph-structured stochastic self-organizing map (graph-SOM) and Markov chain Monte Carlo (MCMC) method.
Download a code espresso-X.X.X.tar.gz or espresso-X.X.X.zip from this repository, and
install by the following command.
install.packages("espresso-X.X.X.tar.gz", repos = NULL, type = "source")
As an alternative way, espresso can be installed directly from GitHub.
library(devtools)
install_github("tmorikuicr/espresso")
Refer to the following documentation for the usage of espresso package.
31-Mar-2022: Vignette
Gene expression data can be downloaded from the following link:
04-Apr-2022: espresso data
To cite your use of the espresso software, please reference the following paper:
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Tomoya Mori, Toshiro Takase, Kuan-Chun Lan, Junko Yamane, Cantas Alev, Azuma Kimura, Kenji Osafune, Jun K. Yamashita, Tatsuya Akutsu, Hiroaki Kitano & Wataru Fujibuchi. eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells. BMC Bioinformatics 24, 252 (2023). https://doi.org/10.1186/s12859-023-05355-4
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Tomoya Mori, Toshiro Takase, Kuan-Chun Lan, Junko Yamane, Cantas Alev, Kenji Osafune, Jun Yamashita, and Wataru Fujibuchi. eSPRESSO: a spatial self-organizing-map clustering method for single-cell transcriptomes of various tissue structure using graph-based networks. bioRxiv. doi: http://doi.org/10.1101/2020.12.31.424948.