Package: conStruct 1.0.7

Gideon Bradburd

conStruct: Models Spatially Continuous and Discrete Population Genetic Structure

A method for modeling genetic data as a combination of discrete layers, within each of which relatedness may decay continuously with geographic distance. This package contains code for running analyses (which are implemented in the modeling language 'rstan') and visualizing and interpreting output. See the paper for more details on the model and its utility.

Authors:Gideon Bradburd [aut, cre]

conStruct_1.0.7.tar.gz
conStruct_1.0.7.zip(r-4.7-x86_64)conStruct_1.0.7.zip(r-4.7-arm64)conStruct_1.0.7.zip(r-4.6-x86_64)conStruct_1.0.7.zip(r-4.6-arm64)
conStruct_1.0.7.tar.gz(r-4.7-arm64)conStruct_1.0.7.tar.gz(r-4.7-x86_64)conStruct_1.0.7.tar.gz(r-4.6-arm64)conStruct_1.0.7.tar.gz(r-4.6-x86_64)
conStruct_1.0.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
conStruct/json (API)

# Install 'conStruct' in R:
install.packages('conStruct', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • onetbb– Parallelism library for C++
  • c++– GNU Standard C++ Library v3
Datasets:
  • conStruct.data - Example dataset used in a 'conStruct' analysis
  • data.block - Example 'data.block' generated by a 'conStruct' analysis

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

onetbbcpp

4.54 score 86 scripts 421 downloads 10 mentions 9 exports 54 dependencies

Last updated from:af976fdf5f. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK400
linux-devel-x86_64OK395
source / vignettesOK621
linux-release-arm64OK329
linux-release-x86_64OK409
windows-devel-arm64OK438
windows-devel-x86_64OK544
windows-release-arm64OK455
windows-release-x86_64OK506
wasm-releaseOK281

Exports:calculate.layer.contributioncompare.two.runsconStructmake.admix.pie.plotmake.all.the.plotsmake.structure.plotmatch.layers.x.runsstructure2conStructx.validation

Dependencies:abindbackportsBHcallrcarolinecheckmateclicodetoolscpp11descdistributionaldoParallelfarverforeachgenericsggplot2gluegridExtragtablegtoolsinlineisobanditeratorslabelinglifecycleloomagrittrmatrixStatsnumDerivotelpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsS7scalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr

How to format data for a conStruct analysis
Format data | conStruct data | Allele frequency data | Geographic sampling coordinates | Geographic distance matrix | Other formats to conStruct | STRUCTURE to conStruct | STRUCTURE data format | Microsatellites
Rendered fromformat-data.Rmdusingknitr::rmarkdown

Last update: 2024-01-09
Started: 2018-09-18

How to visualize the results of a conStruct analysis
Visualize results | Make all the plots | Visualizing estimated admixture proportions | STRUCTURE plots | Order STRUCTURE plots | ADMIXTURE pie plots | Pie plot on a map | Comparing two conStruct runs
Rendered fromvisualize-results.Rmdusingknitr::rmarkdown

Last update: 2019-01-03
Started: 2018-09-18

How to compare conStruct model runs
Model comparison | Cross-validation | How it works | How to run a cross-validation analysis | Visualizing results | Interpreting results | Parallelization | Layer contributions | How to calculate layer contributions | Cross-validation vs. Layer contribution | Advanced options | Specifying data partitions
Rendered frommodel-comparison.Rmdusingknitr::rmarkdown

Last update: 2018-09-18
Started: 2018-09-18

How to run a conStruct analysis
Run conStruct | Running a conStruct analysis | Spatial Model | Nonspatial Model | Other function options | Model diagnosis | MCMC diagnosis | Independent runs | Missing data
Rendered fromrun-conStruct.Rmdusingknitr::rmarkdown

Last update: 2018-09-18
Started: 2018-09-18