Title: Inferring Developmental Chronologies from Single-Cell RNA
Description: An accurate and easy tool for performing trajectory inference on
single cells using single-cell RNA sequencing data. In addition, SCORPIUS
provides functions for discovering the most important genes with respect to
the reconstructed trajectory, as well as nice visualisation tools.
comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood")
Imports: dplyr, dynutils, grDevices, ggplot2 (>= 2.0), magrittr, MASS,
mclust, pbapply, pheatmap, princurve (>= 2.0.2), purrr, ranger,
RColorBrewer, reshape2, splines, stats, tidyr, TSP, utils
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>,
Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)

Imports: dplyr, dynutils (>= 1.0.3), dyndimred (>= 1.0.1), grDevices,
ggplot2 (>= 2.0), MASS, Matrix, mclust, pbapply, pheatmap,
princurve (>= 2.1.3), purrr, ranger, RColorBrewer, reshape2,
Wouter Saelens [ctb] (<https://orcid.org/0000-0002-7114-6248>, zouter)

Description: An accurate and easy tool for performing linear trajectory inference on
princurve (>= 2.1.4), purrr, ranger, RColorBrewer, stats,

Imports: dplyr, dynutils (>= 1.0.3), dynwrap, grDevices, ggplot2 (>=
2.0), lmds, MASS, Matrix, mclust, methods, pbapply, pheatmap,
princurve (>= 2.1.4), purrr, ranger, RANN, RColorBrewer, stats,

Suggests: knitr, rmarkdown, R.rsp, testthat (>= 2.1.0)

princurve (>= 2.1.4), purrr, ranger, RANN, RColorBrewer,

Suggests: covr, knitr, rmarkdown, R.rsp, testthat (>= 2.1.0)

person("Robrecht", "Cannoodt", email = "robrecht.cannoodt@gmail.com", role = c("aut", "cre")))
Imports: dplyr, fitdistrplus, grDevices, ggplot2 (>= 2.0), magrittr,
MASS, mclust, Rcpp, pbapply, pheatmap, princurve, purrr,
ranger, RColorBrewer, reshape2, splines, stats, testthat,

Description: Using principal component analysis as a base model, 'SCOUTer'
offers a new approach to simulate outliers in a simple and precise way.
The user can generate new observations defining them by a pair of well-known
statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2)
statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer'
returns a new set of observations with the desired target properties.
Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and
Maintainer: Alba Gonzalez Cebrian <algonceb@upv.es>
Depends: R (>= 3.5.0), ggplot2, ggpubr, stats
Author: Alba Gonzalez Cebrian [aut, cre],