In priviere/PPBstats: An R package to perform analysis found within PPB programmes

Describe the data {#describe-data-agro}

Once the data have been collected, a first step is to describe them with plot(). Seven types of plot, through the plot_type argument are possible:

• presence abscence matrix that represent the combinaison of germplasm $\times$ location
• histogramm
• barplot, where sd error are displayed
• boxplot
• interaction
• biplot
• radar
• raster
• map

Then you must choose which factor to represent on the x axis (x_axis argument), the factor to display in color (in_col argument), and of course the variables to describe (vec_variables argument).

It is possible to tune the number of factor displayed (nb_parameters_per_plot_x_axis and nb_parameters_per_plot_in_col arguments) and the size of the labels regarding biplot and radar (labels_on and labels_size arguments).

Note that descriptive plots can be done based on version within the data set. See section \@ref(family-4) formore details.

Format the data

Get two data set to look at some examples

data("data_model_GxE")
data_model_GxE = format_data_PPBstats(data_model_GxE, type = "data_agro")

data("data_model_bh_GxE")
data_model_bh_GxE = format_data_PPBstats(data_model_bh_GxE, type = "data_agro")

presence abscence matrix

The presence absence matrix may be different from experimental design planned because of NA. The plot represents the presence/absence matrix of G $\times$ E combinations.

p = plot(
  data_model_GxE, plot_type = "pam",
  vec_variables = c("y1", "y2")
  )
names(p)
p$y1

A score of 3 is for a given germplasm replicated three times in a given environement.

p = plot(
  data_model_bh_GxE, plot_type = "pam",
  vec_variables = c("y1", "y2")
  )
p$y1

Here there are lots of 0 meaning that a lot of germplasm are no in at least two locations. A score of 1 is for a given germplasm in a given location. A score of 2 is for a given germplasm replicated twice in a given location.

histogramm

p = plot(
  data_model_GxE, plot_type = "histogramm",
  vec_variables = c("y1", "y2")
  )
p$y1

barplot

p = plot(
  data_model_GxE, plot_type = "barplot",
  vec_variables = c("y1", "y2"),
  x_axis = "germplasm"
  )

Note that for each element of the following list, there are as many graph as needed with nb_parameters_per_x_axis parameters per graph.

names(p$y1)
p$y1$`germplasm-1|-NA`

p = plot(
  data_model_GxE, plot_type = "barplot",
  vec_variables = c("y1", "y2"),
  x_axis = "germplasm",
  in_col = "location"
  )

Note that for each element of the following list, there are as many graph as needed with nb_parameters_per_x_axis and nb_parameters_per_in_col parameters per graph.

names(p$y1)
p$y1$`germplasm-1|location-1`

boxplot

p = plot(
  data_model_GxE, plot_type = "boxplot",
  vec_variables = c("y1", "y2"),
  x_axis = "germplasm"
  )

Note that for each element of the following list, there are as many graph as needed with nb_parameters_per_x_axis parameters per graph.

names(p$y1)
p$y1$`germplasm-1|-NA`

p = plot(
  data_model_GxE, plot_type = "boxplot",
  vec_variables = c("y1", "y2"),
  x_axis = "germplasm",
  in_col = "location"
  )

Note that for each element of the following list, there are as many graph as needed with nb_parameters_per_x_axis and nb_parameters_per_in_col parameters per graph.

names(p$y1)
p$y1$`germplasm-1|location-1`

interaction

p = plot(
  data_model_GxE, plot_type = "interaction",
  vec_variables = c("y1", "y2"),
  x_axis = "germplasm",
  in_col = "location"
  )

Note that for each element of the following list, there are as many graph as needed with nb_parameters_per_x_axis and nb_parameters_per_in_col parameters per graph.

names(p$y1)
p$y1$`germplasm-1|location-1`

It is also possible to have on the x_axis the date in julian day that have been automatically calculated from format_data_PPBstats(). Note that this is possible only for plot_type = "histogramm", "barplot", "boxplot" and "interaction".

p = plot(
  data_model_GxE, plot_type = "interaction",
  vec_variables = c("y1", "y2"),
  x_axis = "date_julian",
  in_col = "location"
)
p$y1$`y1$date_julian-1|location-1`

biplot

p = plot(
  data_model_GxE, plot_type = "biplot",
  vec_variables = c("y1", "y2", "y3"),
  in_col = "germplasm", labels_on = "germplasm"
  )

The name of the list correspond to the pairs of variables displayed. Note that for each element of the following list, there are as many graph as needed with nb_parameters_per_in_col parameters per graph.

names(p)
p$`y1 - y2`$`-NA|germplasm-1`

radar

Radar can be display either for all variable and a gien factor:

p = plot(
  data_model_GxE, plot_type = "radar",
  vec_variables = c("y1", "y2", "y3"),
  in_col = "location"
  )
p

or for each variable for two given factors:

p = plot(
  data_model_GxE, plot_type = "radar",
  vec_variables = c("y1", "y2", "y3"),
  x_axis = "location",
  in_col = "germplasm"
  )
p$y1

raster

Raster plot can be done for factor variables. Note than when there are no single value for a given x_axis, colums block, X and Y are added in order to have single value.

p = plot(
  data_model_GxE, 
  plot_type = "raster", 
  vec_variables = c("desease", "vigor"), 
  x_axis = "germplasm"
)
p$`germplasm-block-X-Y-9|-NA`

map

You can display map with location if you have data with latitude and longitude for each location. When using map, do not forget to use credit : Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL.

p = plot(
  data_model_GxE, plot_type = "map", labels_on = "location"
)
p$map

and add pies for a given variables

p = plot(
  data_model_GxE, vec_variables = c("y1", "desease"),
  plot_type = "map"
)
p$pies_on_map_y1
p$pies_on_map_desease

priviere/PPBstats documentation built on May 6, 2021, 1:20 a.m.