Package: conStruct 1.0.6

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_1.0.6.tar.gz
conStruct_1.0.6.zip(r-4.7)conStruct_1.0.6.zip(r-4.6)conStruct_1.0.6.zip(r-4.5)
conStruct_1.0.6.tgz(r-4.6-x86_64)conStruct_1.0.6.tgz(r-4.6-arm64)conStruct_1.0.6.tgz(r-4.5-x86_64)conStruct_1.0.6.tgz(r-4.5-arm64)
conStruct_1.0.6.tar.gz(r-4.7-arm64)conStruct_1.0.6.tar.gz(r-4.7-x86_64)conStruct_1.0.6.tar.gz(r-4.6-arm64)conStruct_1.0.6.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
conStruct/json (API)

# Install 'conStruct' in R:
install.packages('conStruct', repos = c('https://gbradburd.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gbradburd/construct/issues

Uses libs:
  • 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:

cpp

8.62 score 38 stars 91 scripts 405 downloads 10 mentions 9 exports 54 dependencies

Last updated from:9dde30b88b. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK377
linux-devel-x86_64OK441
source / vignettesOK601
linux-release-arm64OK386
linux-release-x86_64OK441
macos-release-arm64OK261
macos-release-x86_64OK525
macos-oldrel-arm64OK252
macos-oldrel-x86_64OK590
windows-develOK550
windows-releaseOK498
windows-oldrelOK547
wasm-releaseFAIL207

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

Last update: 2023-12-21
Started: 2018-08-15

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

Last update: 2019-01-02
Started: 2018-09-04

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

Last update: 2018-09-05
Started: 2018-08-21

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

Last update: 2018-09-05
Started: 2018-08-15