README.Rmd

---
output: md_document
---

```{r setup, include=FALSE}
library(knitr)
knitr::opts_chunk$set(warning=FALSE,message=FALSE)
```

# PPBstats

`PPBstats` is a freely available package based on the R software for Participatory Plant Breeding statisticial analyses.
It performs analyses on the data collected during PPB programs at four levels: 

- network of seed management, 
- agronomic trials, 
- organoleptic tests and 
- molecular analyses. 

The objectives of `PPBstats` are

1. to have a single package capable of performing several analyses required for PPB programmes with comprehensive documentation, and 
2. to create a community working on PPB programmes in order to improve the package, exchange on how to process data from PPB programmes and develop good practices. 


## Examples of analysis performed by PPBstats

```{r}
library(PPBstats)
```

### Network of seed management

Descriptive analysis can be done regarding:

- unipart network for seed lots analysis
- unipart network for location analysis
- bipart network analysis

Below an example on unipart network for seed lots analysis:

```{r}
# get data
data(data_network_unipart_sl) 

# format data for the package
net_unipart_sl = format_data_PPBstats(
  type = "data_network",
  data = data_network_unipart_sl, 
  network_part = "unipart", 
  vertex_type =  "seed_lots")

# Display outputs
plot(net_unipart_sl, plot_type = "network", organize_sl = TRUE)
```

Other examples can be found in the book.

### Agronomic trials

Statistical analysis can be done

- To compare different germplasms on each location for selection:
    - classic anova,
    - spatial analysis,
    - mixed models,
    - bayesian hierarchical model intra-location.
- To study response of germplasm over several locations for selection:
    - AMMI and GGE,
    - bayesian hierarchical model G×E.
- To study specific research questions on one farm or more
    - response to selection
    - local adaptation with two models: home away and local foreign
    - intra germplasm variance
- To run multivariate analysis

Below an example on GGE model:

```{r}
# get data
data(data_model_GxE)

# format data for the package
data_model_GxE = format_data_PPBstats(data_model_GxE, type = "data_agro")
```

Once the data are formated, the model is run

```{r}
# run the GGE model
out_gge = model_GxE(data_model_GxE, variable = "y1", gxe_analysis = "GGE")
```

Then, check it, for example with residuals

```{r}
# check if the model went well
out_check_gge = check_model(out_gge)
p_out_check_gge = plot(out_check_gge)
p_out_check_gge$residuals
```

Then, compare means

```{r}
# get mean comparisons
out_mean_comparisons_gge = mean_comparisons(out_check_gge, p.adj = "bonferroni")
p_out_mean_comparisons_gge = plot(out_mean_comparisons_gge)
p_out_mean_comparisons_gge$germplasm$`1`
```

Then, look at biplot

```{r}
# get biplot
out_biplot_gge = biplot_data(out_check_gge)
p_out_biplot_gge = plot(out_biplot_gge)
p_out_biplot_gge$biplot$which_won_where
```



### Organoleptic tests

Sensory analysis can be done on

- hedonic analysis
- napping analysis
- rank analysis

Below an example on hedonic analysis

```{r}
# get data
data(data_hedonic)

# format data for the package
data_hedonic = format_data_PPBstats(data_hedonic, type = "data_organo_hedonic", threshold = 2)
```

```{r}
# descriptive analysis
p_note = plot(data_hedonic, plot_type = "boxplot", x_axis = "germplasm",
               in_col = "location", vec_variables = "note"
               )
p_note$note$`germplasm-1|location-1`


descriptors = data_hedonic$descriptors

p_des = plot(data_hedonic, plot_type = "radar", in_col = "germplasm", 
                         vec_variables = descriptors
                         )
p_des$`all-variables`
```

A model can also be run.


### Molecular analyses

Under development ...

## Tutorial

A full tutorial of `PPBstats` is available in the book on the website.


## Mailing list `ppbstats@framalistes.org`

Exchange information about the R package PPBstats

You can subscribe to this mailing list to have news on the R package `PPBstats` and share questions and remarks

Subscribe : https://framalistes.org/sympa/subscribe/ppbstats