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slendr
View on CRAN: Click
here
Download and install slendr package within the R console
Install from CRAN:
install.packages("slendr")
Install from Github:
library("remotes")
install_github("cran/slendr")
Install by package version:
library("remotes")
install_version("slendr", "1.0.0")
Attach the package and use:
library("slendr")
Maintained by
Martin Petr
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.slendr . https://github.com/bodkan/slendr/issues . https://github.com/bodkan/slendr . slendr results . slendr.pdf . Analyzing non-slendr tree sequences . slendr_1.0.0.tar.gz . slendr_1.0.0.zip . slendr_1.0.0.zip . slendr_1.0.0.zip . slendr_1.0.0.tgz . slendr_1.0.0.tgz . slendr_1.0.0.tgz . slendr_1.0.0.tgz . slendr archive . https://CRAN.R-project.org/package=slendr .
First Published: 2022-08-09
Latest Update: 2023-08-08
Description:
A framework for simulating spatially explicit genomic data which leverages real cartographic information for programmatic and visual encoding of spatiotemporal population dynamics on real geographic landscapes. Population genetic models are then automatically executed by the 'SLiM' software by Haller et al. (2019) <doi:10.1093/molbev/msy228> behind the scenes, using a custom built-in simulation 'SLiM' script. Additionally, fully abstract spatial models not tied to a specific geographic location are supported, and users can also simulate data from standard, non-spatial, random-mating models. These can be simulated either with the 'SLiM' built-in back-end script, or using an efficient coalescent population genetics simulator 'msprime' by Baumdicker et al. (2022) <doi:10.1093/genetics/iyab229> with a custom-built 'Python' script bundled with the R package. Simulated genomic data is saved in a tree-sequence format and can be loaded, manipulated, and summarised using tree-sequence functionality via an R interface to the 'Python' module 'tskit' by Kelleher et al. (2019) <doi:10.1038/s41588-019-0483-y>. Complete model configuration, simulation and analysis pipelines can be therefore constructed without a need to leave the R environment, eliminating friction between disparate tools for population genetic simulations and data analysis.
How to cite:
Martin Petr (2022). slendr: A Simulation Framework for Spatiotemporal Population Genetics. R package version 1.0.0, https://cran.r-project.org/web/packages/slendr. Accessed 22 Apr. 2025.
Previous versions and publish date:
0.2.0 (2022-08-09 14:00), 0.3.0 (2022-08-19 11:20), 0.4.0 (2022-09-30 22:40), 0.5.0 (2023-02-03 00:20), 0.5.1 (2023-03-09 20:40), 0.6.0 (2023-06-07 12:20), 0.7.0 (2023-06-26 18:30), 0.7.1 (2023-07-14 21:10), 0.7.2 (2023-08-08 11:50), 0.8.0 (2023-12-07 11:50), 0.8.1 (2024-01-15 16:20), 0.9.0 (2024-02-08 09:10), 0.9.1 (2024-02-22 00:20)
Other packages that cited slendr R package
View slendr citation profile
Other R packages that slendr depends,
imports, suggests or enhances
Complete documentation for slendr
Functions, R codes and Examples using
the slendr R package
Some associated functions: animate_model . area . as.phylo.slendr_phylo . check_dependencies . check_env . clear_env . compile_model . distance . expand_range . explore_model . gene_flow . join . move . msprime . overlap . pipe . plot_map . plot_model . population . print.slendr_pop . print.slendr_ts . read_model . region . reproject . resize . schedule_sampling . set_dispersal . set_range . setup_env . shrink_range . slendr . slim . subtract . ts_afs . ts_ancestors . ts_coalesced . ts_descendants . ts_divergence . ts_diversity . ts_draw . ts_edges . ts_eigenstrat . ts_f4ratio . ts_fst . ts_genotypes . ts_load . ts_metadata . ts_mutate . ts_nodes . ts_phylo . ts_recapitate . ts_samples . ts_save . ts_segregating . ts_simplify . ts_table . ts_tajima . ts_tree . ts_vcf . world .
Some associated R codes: compilation.R . geometry.R . interface.R . print.R . shiny.R . slendr-package.R . tree-sequences.R . utils.R . visualization.R . zzz.R . Full slendr package functions and examples
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