README_old.md
In allogamous/EnvRtype: Envirotyping Tools for Crop Research and Genetic Improvment

EnvRtype: Envirotyping Tools in R

An Interplay between Quantitative Genetics and Ecophysiology for GxE analysis.

--------------------------------------------- ## Background > Envirotyping has proven useful in identifying the non-genetic drivers of phenotypic adaptation in plants cultivaded in diverse growing conditions. Combined with phenotyping and genotyping data, the use of envirotyping data may leverage the molecular breeding strategies to cope with environmental changing scenarios. Over the last ten years, this data has been incorporated in genomic-enabled prediction models aiming to better model genotype x environment interaction (GE) as a function of reaction-norm. However, there is difficult for most breeders to deal with the interplay between envirotyping, ecophysiology, and genetics. > It also can be useful for several fields of agricultural, livestook and ecology research, by delivering high-quality environmental information and environmental grouping appraoches. > Here we present the EnvRtype R package as a new toolkit developed to facilitate the interplay between envirotyping and fields of plant research such as genomic prediction. This package offers three modules: (1) collection and processing data set, (2) environmental characterization, (3) build of ecophysiological enriched predictive models accounting for three different structures of reaction-norm over different sources of genomic relatedness. Thus, EnvRtype is useful for exploratory purposes and predctive breeding for multiple growing conditions.

--------------------------------------------- ## Resources > The envirotyping pipeline provided by EnvRtype consists in three modules (sections 2-4). Collectively, the EnvRtyping functions generate a simple workflow to collect, process and integrates envirotyping data into several fields of agricultural research, specially for predictive breeding that may include the use of genomic x enviromic relatedness information.

**Main Functions** * [1. Install and Required Packages](#Instal) * [Maintence (from December 19th to January 10th) 2. Environmental Sensing Module](https://github.com/allogamous/EnvRtype/blob/master/Module1.md) * [Maintence (from December 19th to January 10th) 3. Environmental Characterization Module](https://github.com/allogamous/EnvRtype/blob/master/Module2.md) * [Maintence (from December 19th to January 10th) 4. Reaction-Norm Module](https://github.com/allogamous/EnvRtype/blob/master/Module3.md) **Tutorials** * [Envirotyping pipeline](https://github.com/allogamous/EnvRtype/blob/master/Enviromic_pipeline.md) * [Genomic Prediction using Environmental Covariates](https://github.com/allogamous/EnvRtype/blob/master/Genomic%20Prediction.md) **Information** * [Authorship](#P4) * [Acknowledgments](#P5) * [Publications](#P6) * [Updates and Maintence](#P7)

## Install ### Using devtools in R wzxhzdk:0 ### Required packages > * **[EnvRtype](https://github.com/allogamous/EnvRtype)** > * **[raster](https://CRAN.R-project.org/package=raster)** > * **[nasapower](https://github.com/ropensci/nasapower)** > * **[BGGE](https://github.com/italo-granato/BGGE)** > * **[foreach](https://github.com/cran/foreach)** > * **[doParalell](https://github.com/cran/doparallel)** wzxhzdk:1 [Menu](#menu)

------------------------------------------------------------ ## Authorship This package is a initiative from the [Allogamous Plant Breeding Lab (University of São Paulo, ESALQ/USP, Brazil)](http://www.genetica.esalq.usp.br/en/lab/allogamous-plant-breeding-laboratory). **Developer** > * [Germano Costa Neto](https://github.com/gcostaneto), PhD Candidate in Genetics and Plant Breeding **Maintence** > * [Germano Costa Neto](https://github.com/gcostaneto), PhD Candidate in Genetics and Plant Breeding > * [Giovanni Galli](https://github.com/giovannigalli), PhD in Genetics and Plant Breeding > * [Humberto Fanelli](https://github.com/humbertofanelli), PhD in Genetics and Plant Breeding

------------------------------------------------------------ ## Acknowledgments > * [Giovanni Galli](https://github.com/giovannigalli), PhD in Genetics and Plant Breeding > * [Humberto Fanelli](https://github.com/humbertofanelli), PhD in Genetics and Plant Breeding > * **Jose Crossa**, Biometrics and Statistic Unit at CIMMYT. > * [Roberto Fritsche-Neto](roberto.neto@usp.br), Professor in Genetics and Plant Breeding, Head of Allogamous Plant Breedig Lab (ESALQ/USP) > * [University of São Paulo (ESALQ/USP)](https://www.esalq.usp.br/) > * [Conselho Nacional de Desenvolvimento Científico e Tecnológico](http://www.cnpq.br/) for the PhD scholarship granted to the authors of the package > * [Pedro L. Longhin](https://github.com/pedro-longhin) for additional support in Git Hub

------------------------------------------------------------ ## Publications Costa-Neto G, Galli G, Fanelli H, Crossa J, Fritsche-Neto R (2020). EnvRtype : a software to interplay enviromics and quantitative genomics in agriculture. bioRxiv [in press](https://www.biorxiv.org/content/10.1101/2020.10.14.339705v1) Galli G, Horne DW, Collins SD, Jung J, Chang A, Fritsche‐Neto R, et al. (2020). Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum. **Plant Phenome** J 3: 1–14. Costa-Neto G, Fritsche-Neto R, Crossa J (2020). Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials. **Heredity** (Edinb).

--------------------------------------------- ## Updates and Maintence > The current version of the pacakge is 0.1.9. > From December 15th 2020 to January 10th 2021 this page will be under maintence. This means that we are now working in several updates and some changes will be made in some functions.