{"id":26717780,"url":"https://github.com/alexkychen/assignpop","last_synced_at":"2025-04-14T02:33:05.679Z","repository":{"id":56934484,"uuid":"61150304","full_name":"alexkychen/assignPOP","owner":"alexkychen","description":"Population Assignment using Genetic, Non-genetic or Integrated Data in a Machine-learning Framework.    Methods in Ecology and Evolution. 2018;9:439–446. 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It employs supervised machine-learning methods to evaluate the discriminatory power of your data collected from source populations, and is able to analyze **large genetic, non-genetic, or integrated (genetic plus non-genetic) data** sets. This framework is designed for solving the upward bias issue discussed in previous studies. Main features are listed as follows.\r\n\r\n- Use principle component analysis (PCA) for dimensionality reduction (or data transformation)\r\n- Use Monte-Carlo cross-validation to estimate mean and variance of assignment accuracy\r\n- Use *K*-fold cross-validation to estimate membership probability\r\n- Allow to resample various sizes of training datasets (proportions or fixed numbers of individuals and proportions of loci)\r\n- Allow to choose from various proportions of training loci either randomly or based on locus *Fst* values\r\n- Provide several machine-learning classification algorithms, including LDA, SVM, naive Bayes, decision tree, and random forest, to build tunable predictive models.\r\n- Output results in publication-quality plots that can be modified using ggplot2 functions\r\n\r\n## Install assignPOP\r\nYou can install the released version from CRAN or the up-to-date version from this Github respository.\r\n\r\n- To install from CRAN\r\n  * Simply enter `install.packages(\"assignPOP\")` in your R console\r\n\r\n- To install from Github\r\n  * step 1. Install devtools package by entering `install.packages(\"devtools\")`\r\n  * step 2. Import the library, `library(devtools)`\r\n  * step 3. Then enter `install_github(\"alexkychen/assignPOP\")` \r\n\r\nNote: When you install the package from Github, you may need to install additional packages before the assignPOP can be successfully installed. Follow the hints that R provided and then re-run `install_github(\"alexkychen/assignPOP\")`.\r\n\r\n## Package tutorial\r\nPlease visit our tutorial website for more infomration\r\n* [http://alexkychen.github.io/assignPOP/](http://alexkychen.github.io/assignPOP/)\r\n\r\n## What's new\r\nChanges in ver. 1.3.0 (2024.3.13)\r\n- Update accuracy.plot - adjust ggplot's aes_string() due to its deprecation. \r\n- Update testthat test_accuracy and test_membership to meet ggplot2 3.5.0 requirements\r\n\r\n\u003cdetails\u003e\r\n\u003csummary\u003eHistory\u003c/summary\u003e\r\n\r\nChanges in ver. 1.2.4 (2021.10.27)\r\n- Update membership.plot - add argument 'plot.k' and 'plot.loci' to skip related question prompt.\r\n\r\nChanges in ver. 1.2.3 (2021.8.17)\r\n- Update assign.X - (1)Add argument 'common' to specify whether stopping the analysis when inconsistent features between data sets were found. (2)Add argument 'skipQ' to skip data type checking on non-genetic data. (3)Modify argument 'mplot' to handle membership probability plot output.\r\n\r\nChanges in ver. 1.2.2 (2020.11.6)\r\n- Update read.Genepop and read.Structure - locus has only one allele across samples will be kept. Use reduce.allele to remove single-allele or low variance loci.\r\n- In ver. 1.2.1, errors might be generated when running assign.MC (and other assignment test functions) due to existence of single-allele loci. (fixed in ver. 1.2.2)\r\n\r\nChanges in ver. 1.2.1 (2020.8.24)\r\n- Update read.Genepop to increase file reading speed (~40 times faster)\r\n- Update read.Structure to increase file reading speed (~90 times faster)\r\n- read.Structure now also can handle triploid and tetraploid organisms (see arg. ploidy)\r\n- fix bug in allele.reduce to handle small p threshold across all loci\r\n\r\nChanges in ver. 1.2.0 (2020.7.24)\r\n- Add codes to check model name in assign.MC, assign.kfold, assign.X\r\n- Add text to SVM description\r\n- Fix cbind/stringsAsFactors issues in several places for R 4.0\r\n- Able to inject arugments used in models (e.g., gamma in SVM) \r\n\r\nChanges in ver. 1.1.9 (2020.3.16)\r\n- Fix input non-genetic data (x1) error in assign.X\r\n\r\nChanges in ver. 1.1.8  (2020.2.28)\r\n- update following functions to work with R 4.0.0\r\n- accuracy.MC, accuracy.kfold, assign.matrix, compile.data, membership.plot\r\n- add stringsAsFactor=T to read.table and read.csv\r\n- temporarily turn off testthat due to its current failure to pass test in Debian system\r\n\r\nChanges in ver. 1.1.7  (2019.8.26)\r\n- add broken-stick method for principal component selection in assign.MC, assign.kfold, and assign.X functions\r\n- update accuracy.MC, accuracy.kfold, assign.matrix to handle missing levels of predicted population in test results\r\n- update assign. and accuracy. functions to handle numeric population names\r\n\r\nChanges in ver. 1.1.6  (2019.6.8)\r\n- fix multiprocess issue in assign.kfold function\r\n\r\nChanges in ver. 1.1.5  (2018.3.23)\r\n- Update assign.MC \u0026 assign.kfold to detect pop size and train.inds/k.fold setting\r\n- Update accuracy.MC \u0026 assign.matrix to handle test individuals not from every pop\r\n- Slightly modify levels method in accuracy.kfold\r\n- fix bugs in accuracy.plot for K-fold results\r\n- fix membership.plot title positioning and set text size to default\r\n\r\nChanges in ver. 1.1.4  (2018.3.8)\r\n- Fix missing assign.matrix function\r\n\r\nChanges in ver. 1.1.3  (2017.6.15)\r\n- Add unit tests (using package testthat)\r\n\r\nChanges in ver. 1.1.2  (2017.5.13)\r\n- Change function name read.genpop to read.Genepop; Add function read.Structure.\r\n- Update read.genpop function, now can read haploid data\r\n\u003c/details\u003e\r\n\r\n## Cite this package\r\nChen, K. Y., Marschall, E. A., Sovic, M. G., Fries, A. C., Gibbs, H. L., \u0026 Ludsin, S. A. (2018). assign POP: An R package for population assignment using genetic, non-genetic, or integrated data in a machine-learning framework. *Methods in Ecology and Evolution*. 9(2)439-446. https://doi.org/10.1111/2041-210X.12897\r\n\r\n[Papers citing our package](https://scholar.google.com/scholar?oi=bibs\u0026hl=en\u0026cites=14878258167162189944\u0026as_sdt=5)\r\n\r\n## Previous version\r\nPrevious packages can be found and downloaded at the [releases page](https://github.com/alexkychen/assignPOP/releases)\r\n\r\n## Version compatibility (2020.7.24)\r\nassignPOP version 1.1.9 and earlier are not fully compatible with newly released R 4.0.0. \r\nIf you're using R 4.0.0 (or newer), please update your assignPOP to 1.2.0.  \r\n\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexkychen%2Fassignpop","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falexkychen%2Fassignpop","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexkychen%2Fassignpop/lists"}