estimatebreed

https://github.com/willyanjnr/estimatebreed

Repository

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# EstimateBreed  


![Lifecycle: experimental](https://lifecycle.r-lib.org/articles/figures/lifecycle-stable.svg)


EstimateBreed is an R package designed to perform analyses and estimate environmental covariates and genetic parameters related to selection strategies and the development of superior genotypes. The package offers two main functionalities: 

- **Prediction models** for environmental covariates and processes.
- **Estimation of genetic parameters** and selection strategies for developing superior genotypes.

## Installation

You can install the development version of EstimateBreed from [GitHub](https://github.com/) with:

``` r
if (!requireNamespace("pak", quietly = TRUE)) {
  install.packages("pak")
}
pak::pak("willyanjnr/EstimateBreed")
```

## Genotype selection

Obtain the genetic selection index for resilience (ISGR) for selecting genotypes for environmental stressors, as described by [Bandeira et al. (2024)](https://www.cropj.com/Carvalho_18_12_2024_825_830.pdf).

``` r
library(EstimateBreed)

#Obtain environmental deviations
data("desvamb")
DPclim <- with(desvamb,desv_clim(ENV,TMED,PREC))
DPclim
# A tibble: 3 × 5
#  ENV   STMED TMEDR SPREC PRECIR
#       
# 1 E1     2.65  24.8  5.46   339.
# 2 E2     3.65  23.8  5.27   344.
# 3 E3     2.81  24.5  5.47   362.

#Get the ISGR
data("genot")
isgr_index <- with(genot, isgr(GEN,ENV,NG,MG,CICLO))
isgr_index
#    Gen Env      ISGR
# 26 L454  E1  6.489941
# 22 L455  E1  7.084315
# 19 L541  E1  7.653157
# 18 L367  E1  7.862185
# 16 L380  E1  8.329434
# 12 L393  E1  9.638909
# 10 L439  E1 10.552056
# 28 L298  E3 12.209433
# 30 L358  E2 23.347984
# 29 L346  E2 23.793351
# 27 L195  E2 24.719927
# 25 L179  E2 25.747317
# 24 L359  E2 26.300686
# 23 L345  E2 26.886419
# 1  L445  E1 27.255375
# 21 L185  E2 28.211433
# 20 L310  E2 28.942165
# 17 L178  E2 31.418785
# 15 L261  E2 33.424611
# 14 L269  E2 34.605133
# 13 L209  E2 35.959423
# 11 L263  E2 39.127798
# 9  L201  E2 43.145922
# 8  L299  E2 45.686042
# 7  L152  E2 48.926278
# 6   L26  E2 52.988109
# 5  L166  E2 57.596139
# 4  L155  E2 64.251152
# 3  L277  E2 74.756384
# 2  L162  E2 86.543916
```

Selection of transgressive genotypes with the selection differential (mean and standard deviations).
``` r

library(EstimateBreed)

Gen <- paste0("G", 1:20)
Var <- round(rnorm(20, mean = 3.5, sd = 0.8), 2)
Control <- rep(3.8, 20)

data <- data.frame(Gen,Var,Control)

with(data,transg(Gen,Var,Control))
```

Returns the general parameters and the genotypes selected for each treshold. 
Also plot a representative graph of the selected genotypes based on the mean and standard deviations.
``` r
---------------------------------------------------------------------
Selection of Transgressive Genotypes - Selection Differential (SD)
---------------------------------------------------------------------
Parameters:
---------------------------------------------------------------------
Overall Mean         : 3.566
Control Mean         : 3.800
Standard Deviation   : 0.603
Mean + 1SD           : 4.169
Mean + 2SD           : 4.771
Mean + 3SD           : 5.374

---------------------------------------------------------------------
Genotypes above each threshold:
---------------------------------------------------------------------
Genotypes above Control Mean : G4, G7, G8, G9, G12, G14,
  G20 
Genotype above Overall Mean : G4, G7, G8, G9, G12, G14,
  G16, G18, G20 
Genotypes above Mean + 1SD : G7, G9, G20 
Genotypes above Mean + 2SD : G7 
Genotypes above Mean + 3SD     : None
---------------------------------------------------------------------
```

## Estimation of environmental variables and processes

Predict ∆T to determine the ideal times to apply agricultural pesticides.
``` r

library(EstimateBreed)

# Forecasting application conditions
tdelta(-53.696944444444,-28.063888888889,type=1,days=10)

# Retrospective analysis of application conditions
tdelta(-53.6969,-28.0638,type=2,days=10,dates=c("2023-01-01","2023-05-01"))
```

Estimation of soybean plastochron using average air temperature and number of nodes
``` r
library(EstimateBreed)
data("pheno")

with(pheno, plast(GEN,TMED,EST,NN,habit="ind",plot=TRUE))
```
#

## Documentation
Complete documentation can be found when using the package within R.

## Citing
When citing this package, please use,
``` r
library(EstimateBreed)
citation("EstimateBreed")

To cite package ‘EstimateBreed’ in publications use:

  Willyan Jr. A. Bandeira, Ivan R. Carvalho, Murilo V. Loro, Leonardo
  C. Pradebon, José A. G. da Silva (2025). _EstimateBreed: Estimation
  of Environmental Variables and Genetic Parameters_. R package
  version 0.1.0, .

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {EstimateBreed: Estimation of Environmental Variables and Genetic Parameters},
    author = {{Willyan Jr. A. Bandeira} and {Ivan R. Carvalho} and {Murilo V. Loro} and {Leonardo C. Pradebon} and {José A. G. da Silva}},
    year = {2025},
    note = {R package version 0.1.0},
    url = {https://github.com/willyanjnr/EstimateBreed},
  }
```

## Getting Help
- If you find any errors, please make a report with the commands used so that we can repeat, check and adjust the functions! Send it to [github](https://github.com/willyanjnr/EstimateBreed/issues) or send an email to bandeira.wjab@gmail.com.

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