The goal of hagis is to provide analysis tools for plant pathogens with gene-for-gene interactions in the R programming language that the original Habgood-Gilmour Spreadsheet, HaGiS, (Herrmann, Löwer and Schachtel) provided.
This R package has been published in MPMI as a resource announcement (McCoy et al. 2019). You may wish to refer to that paper for further information on this package.
hagis was initially created for Phytophthora sojae surveys by Austin McCoy and Zachary Noel at Michigan State University in the US, where the disease has been managed primarily via deployment of resistance genes (Rps genes, resistance to P. sojae) in commercial soybean cultivars and by the application of fungicide seed treatments. However, repeated use of resistance genes can cause populations to adapt over time rendering these resistance genes ineffective. To determine current effectiveness of resistance genes for managing P. sojae, state-wide surveys (in the US) are conducted to determine the pathotype (previously referred to as “race”) structure within sampled population of P. sojae.
However, the package is not only useful for P. sojae work. It was built to be useful for other plant pathogen gene-for-gene interaction systems, e.g. rusts or canola blackleg, Leptosphaeria maculans. The goal of this package is to provide all the necessary analyses needed when conducting a pathotype surveys, including: distribution of susceptibilities (effective and non-effective resistance genes), distribution of pathotype complexities with statistics, pathotype frequency distribution, as well as diversity indices for pathotypes in an efficient and reproducible manner.
New users are encouraged to visit the documentation, https://openplantpathology.github.io/hagis/articles/hagis.html, for detailed information on how to use hagis along with working examples using a built-in data set.
A stable version of hagis is available from CRAN.
install.packages("hagis")
A development version is available from from GitHub. If you wish to install the development version that may have new features or bug fixes before the CRAN version does (but also may not work properly), please install the remotes package, available from CRAN. We strive to keep the main branch on GitHub functional and working properly.
if (!require("remotes")) {
install.packages("remotes", repos = "http://cran.rstudio.com/")
library("remotes")
}
install_github("openplantpathology/hagis", build_vignettes = TRUE)
When you use hagis, please cite by using:
citation("hagis")
##
## Thank you for citing `hagis`. To cite `hagis` in publications, please
## use both the MPMI citation and the package version citation for
## reproducibility purposes so changes. to the package over time may be
## accounted for in publications.
##
## Austin Glenn McCoy, Zachary A. Noel, Adam H. Sparks and Martin
## Chilvers (2019). `hagis', an R Package Resource for Pathotype
## Analysis of Phytophthora sojae Populations Causing Stem and Root Rot
## of Soybean. Molecular Plant-Microbe Interactions 32.12 (Nov 2019) p.
## 1574-1576. DOI: 10.1094/MPMI-07-19-0180-A
##
## McCoy AG, Noel ZA, Sparks AH, Chilvers MI (2021). _hagis: Analysis of
## Plant Pathogen Pathotype Complexities, Distributions and Diversity_.
## doi:10.5281/zenodo.2619820 <https://doi.org/10.5281/zenodo.2619820>,
## R package version 3.1.3,
## <https://openplantpathology.github.io/hagis/>.
##
## To see these entries in BibTeX format, use 'print(<citation>,
## bibtex=TRUE)', 'toBibtex(.)', or set
## 'options(citation.bibtex.max=999)'.
Please note that the hagis project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Herrmann, Löwer and Schachtel. (1999), A new tool for entry and analysis of virulence data for plant pathogens. Plant Pathology, 48: 154-158. DOI: 10.1046/j.1365-3059.1999.00325.x
McCoy, Noel, Sparks and Chilvers. (2019). ‘hagis’, an R Package Resource for Pathotype Analysis of Phytophthora sojae Populations Causing Stem and Root Rot of Soybean. Molecular Plant-Microbe Interactions 32.12 (Nov 2019) p. 1574-1576. DOI: 10.1094/MPMI-07-19-0180-A