The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Fast maximum-likelihood phylogeny inference from noisy single-cell data using the 'ScisTree' algorithm by Yufeng Wu (2019) <doi:10.1093/bioinformatics/btz676>. 'scistreer' provides an 'R' interface and improves speed via 'Rcpp' and 'RcppParallel', making the method applicable to massive single-cell datasets (>10,000 cells).
| Version: | 1.2.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | ape, dplyr, ggplot2, ggtree, igraph, parallelDist, patchwork, phangorn, Rcpp, reshape2, RcppParallel, RhpcBLASctl, stringr, tidygraph |
| LinkingTo: | Rcpp, RcppArmadillo, RcppParallel |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2023-06-15 |
| DOI: | 10.32614/CRAN.package.scistreer |
| Author: | Teng Gao [cre, aut], Evan Biederstedt [aut], Peter Kharchenko [aut], Yufeng Wu [aut] |
| Maintainer: | Teng Gao <tgaoteng at gmail.com> |
| License: | GPL-3 |
| URL: | https://github.com/kharchenkolab/scistreer, https://kharchenkolab.github.io/scistreer/ |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Materials: | README |
| CRAN checks: | scistreer results |
| Reference manual: | scistreer.pdf |
| Package source: | scistreer_1.2.0.tar.gz |
| Windows binaries: | r-devel: scistreer_1.2.0.zip, r-release: scistreer_1.2.0.zip, r-oldrel: scistreer_1.2.0.zip |
| macOS binaries: | r-release (arm64): scistreer_1.2.0.tgz, r-oldrel (arm64): scistreer_1.2.0.tgz, r-release (x86_64): scistreer_1.2.0.tgz, r-oldrel (x86_64): scistreer_1.2.0.tgz |
| Old sources: | scistreer archive |
| Reverse imports: | numbat |
Please use the canonical form https://CRAN.R-project.org/package=scistreer to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.