data.table, DIZtools, DIZutils (>= 0.0.13), future,
future.apply, jsonlite, kableExtra, knitr, magrittr, parsedate,
rmarkdown, stats, tinytex, utils

data.table, DIZtools (>= 0.0.5), DIZutils (>= 0.1.0), future,
future.apply, jsonlite, kableExtra, knitr, magrittr, parsedate,
rmarkdown, stats, tinytex, utils

data.table, DIZtools (>= 0.0.5), DIZutils (>= 0.1.1), future,
future.apply, jsonlite, kableExtra, knitr, magrittr, parsedate,
rmarkdown, stats, tinytex, utils

Joint Dimension Reduction and Spatial Clustering
c(person(given = "Wei",
family = "Liu",
role = c("aut", "cre"),
email = "wei.liu@duke-nus.edu.sg"),
person(given = "Xingjie",
family = "Shi",
role = "aut"),
person(given = "Jin",
family = "Liu",
role = "aut"))
Wei Liu [aut, cre],
Xingjie Shi [aut],
Jin Liu [aut]
Joint dimension reduction and spatial clustering is conducted for
Single-cell RNA sequencing and spatial transcriptomics data, and more details can be referred to
Yi Yang, Xingjie Shi, Wei Liu et al. (2021) <doi:10.1101/2021.06.05.447181>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.
CompQuadForm, cowplot, ggplot2, GiRaF, MASS, Matrix, mclust,
methods, purrr, RColorBrewer, Rcpp (>= 1.0.5), Seurat, stats

Joint dimension reduction and spatial clustering is conducted for
Single-cell RNA sequencing and spatial transcriptomics data, and more details can be referred to
Wei Liu, Xu Liao, Xiang Zhou, Shijie Shi and Jin Liu. (2021) <doi:10.1101/2021.12.25.474153>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.
CompQuadForm, cowplot, ggplot2, GiRaF, MASS, Matrix, mclust,
methods, purrr, S4Vectors, RColorBrewer, Rcpp (>= 1.0.5),
Seurat, stats

c(person(given = "Wei",
family = "Liu",
role = c("aut", "cre"),
email = "wei.liu@duke-nus.edu.sg"),
person(given = "Yi",
family = "Yang",
role = c("aut")),
person(given = "Xingjie",
family = "Shi",
role = "aut"),
person(given = "Jin",
family = "Liu",
role = "aut"))
Wei Liu [aut, cre],
Yi Yang [aut],
Xingjie Shi [aut],
Jin Liu [aut]
Joint dimension reduction and spatial clustering is conducted for
Single-cell RNA sequencing and spatial transcriptomics data, and more details can be referred to
Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou, Xingjie Shi and Jin Liu. (2022) <doi:10.1101/2021.12.25.474153>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.