Last updated: 2022-03-08

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Knit directory: HenriqueDGen/

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Introduction

Phenotypic data

Descriptive and deviance analysis were performed to verify the distribution and the genotypic effects for resistance to foliar diseases.

Foliar Disease data

suppressMessages(library(tidyverse))
library(here)
here() starts at /Users/lbd54/Documents/GitHub/HenriqueDGen
suppressMessages(library(reactable))

# Data read by R using here package to allow the read in any computer with different directory path
PhenoData <- readRDS(here::here("data", "DadosFenotipicos.RDS"))
# Add the control information for the Mixed Models analysis
control <- names(table(PhenoData$accession_name)[table(PhenoData$accession_name) > 30])
PhenoData$control <- ifelse(PhenoData$accession_name %in% control, PhenoData$accession_name, "999") 
PhenoData$new <- ifelse(PhenoData$accession_name %in% control, 0, 1)

# Change the Disease names to english abbreviations
colnames(PhenoData)[7:10] <- c("Anth", "WhLS", "BrLS", "BlLS")

Table 1. Phenotypic data for resistance to foliar disease evaluated at the Cassava Germplasm Bank of EMBRAPA, data collected in 2021.

Anthracnosis (Anth), White Leaf spot (WhLS), Brown Leaf spot (BrLS), Blight Leaf Spot (BlLS).

lnfUtl <- colnames(PhenoData)[c(1:4, 11:12)]
PhenoData$talhao_number <- NULL
PhenoData$Idade <- NULL
traits <- colnames(PhenoData)[!colnames(PhenoData) %in% lnfUtl]
PhenoData2 <- PhenoData %>% gather(key = traits, value = Y, -all_of(lnfUtl))

saveRDS(PhenoData2, here::here("output", "DadosFenotipicosv2.RDS"))

Table 2. Data entry for the descriptive analysis and mixed models for resistance of foliar disease in cassava.

Anthracnosis (Anth), White Leaf spot (WhLS), Brown Leaf spot (BrLS), Blight Leaf Spot (BlLS).

Yield Traits

library(reshape2)

Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':

    smiths
DadosProdutivos <- read.table(here::here("data", "Dados Produtivos 2011-2021.CSV"), header = T, sep = ",",
                              na.strings = "NA")

head(DadosProdutivos)
   Ano      Campo Local Genotipos.BGM Genotipos Delineamento Controle Bloco
1 2011 Agroverde1 CNPMF      BGM-0023  BGM-0023          DBC        0     1
2 2011 Agroverde1 CNPMF      BGM-0023  BGM-0023          DBC        0     2
3 2011 Agroverde1 CNPMF      BGM-0023  BGM-0023          DBC        0     3
4 2011 Agroverde1 CNPMF      BGM-0025  BGM-0025          DBC        0     1
5 2011 Agroverde1 CNPMF      BGM-0025  BGM-0025          DBC        0     2
6 2011 Agroverde1 CNPMF      BGM-0025  BGM-0025          DBC        0     3
  Linha Coluna Stand  AP APsF DMC   PTR   PRC  PRNC   PPA NR Vigor Vigor45D
1    27      7    18 128   NA  NA 47.81 41.56  6.25 46.88 NA    NA       NA
2    25     14    17 229   NA  NA 45.94 35.06 10.88 49.06 NA    NA       NA
3    16     24    20 268   NA  NA 71.25 59.95 11.30 56.56 NA    NA       NA
4     7      2    16 174   NA  NA 21.25 13.96  7.29 21.25 NA    NA       NA
5     4     11    17 202   NA  NA 25.00 19.91  5.09 27.50 NA    NA       NA
6     3     20    17 230   NA  NA 16.25  9.19  7.06 29.38 NA    NA       NA
  Vigor6M Vigor12M
1      NA       NA
2      NA       NA
3      NA       NA
4      NA       NA
5      NA       NA
6      NA       NA
colnames(DadosProdutivos)[c(4,12:23)] <- c("Genotipo_BGM","AP", "APsF","DMC",
                                            "PTR","PRC", "PRNC","PPA","NR","Vigor","Vigor45D","Vigor6M","Vigor12M")

DadosPhen2 <- DadosProdutivos %>% dplyr::select(-c(AP, APsF, DMC, PRC, PRNC))

head(DadosPhen2)
   Ano      Campo Local Genotipo_BGM Genotipos Delineamento Controle Bloco
1 2011 Agroverde1 CNPMF     BGM-0023  BGM-0023          DBC        0     1
2 2011 Agroverde1 CNPMF     BGM-0023  BGM-0023          DBC        0     2
3 2011 Agroverde1 CNPMF     BGM-0023  BGM-0023          DBC        0     3
4 2011 Agroverde1 CNPMF     BGM-0025  BGM-0025          DBC        0     1
5 2011 Agroverde1 CNPMF     BGM-0025  BGM-0025          DBC        0     2
6 2011 Agroverde1 CNPMF     BGM-0025  BGM-0025          DBC        0     3
  Linha Coluna Stand   PTR   PPA NR Vigor Vigor45D Vigor6M Vigor12M
1    27      7    18 47.81 46.88 NA    NA       NA      NA       NA
2    25     14    17 45.94 49.06 NA    NA       NA      NA       NA
3    16     24    20 71.25 56.56 NA    NA       NA      NA       NA
4     7      2    16 21.25 21.25 NA    NA       NA      NA       NA
5     4     11    17 25.00 27.50 NA    NA       NA      NA       NA
6     3     20    17 16.25 29.38 NA    NA       NA      NA       NA
DadosPhenfin <- reshape2::melt(data = DadosPhen2,id.vars = c("Ano","Campo","Local","Delineamento","Controle","Genotipo_BGM","Genotipos","Bloco","Linha", "Coluna", "Stand"),
                                     variable.name = "Trait",
                                     value.name = "Value") %>%
  filter(!is.na(Value)) %>% 
  dplyr::mutate(Ano = Ano,
         Campo = Campo,
         Local = Local,
         trial = match(paste(Ano, Campo, Local, sep = "."), unique(paste(Ano, Campo, Local, sep = "."))),
         studyDesign = Delineamento,
         clone = Genotipo_BGM,
         rep = Bloco,
         check = ifelse(Controle == "1", clone, "999"),
         check = ifelse(clone %in% unique(check), clone, "999"),
         new = ifelse(check != "999", 0, 1),
         y = Value, .keep = "unused") %>% dplyr::select(-c("Genotipos")) %>%
  filter(Trait != "NR" | (Trait=="NR" & y < 30))
head(DadosPhenfin)
   Ano      Campo Local Linha Coluna Stand Trait trial studyDesign    clone rep
1 2011 Agroverde1 CNPMF    27      7    18   PTR     1         DBC BGM-0023   1
2 2011 Agroverde1 CNPMF    25     14    17   PTR     1         DBC BGM-0023   2
3 2011 Agroverde1 CNPMF    16     24    20   PTR     1         DBC BGM-0023   3
4 2011 Agroverde1 CNPMF     7      2    16   PTR     1         DBC BGM-0025   1
5 2011 Agroverde1 CNPMF     4     11    17   PTR     1         DBC BGM-0025   2
6 2011 Agroverde1 CNPMF     3     20    17   PTR     1         DBC BGM-0025   3
  check new     y
1   999   1 47.81
2   999   1 45.94
3   999   1 71.25
4   999   1 21.25
5   999   1 25.00
6   999   1 16.25
saveRDS(object = DadosPhenfin, file = here::here("output", "DadosFenotipicos.rds"))

Dendrogram and Shannon-Weaver Index


sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Big Sur 11.6.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] reshape2_1.4.4  reactable_0.2.3 here_1.0.1      forcats_0.5.1  
 [5] stringr_1.4.0   dplyr_1.0.8     purrr_0.3.4     readr_2.1.2    
 [9] tidyr_1.2.0     tibble_3.1.6    ggplot2_3.3.5   tidyverse_1.3.1

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8        lubridate_1.8.0   assertthat_0.2.1  rprojroot_2.0.2  
 [5] digest_0.6.29     utf8_1.2.2        plyr_1.8.6        reactR_0.4.4     
 [9] R6_2.5.1          cellranger_1.1.0  backports_1.4.1   reprex_2.0.1     
[13] evaluate_0.15     httr_1.4.2        pillar_1.7.0      rlang_1.0.1      
[17] readxl_1.3.1      rstudioapi_0.13   whisker_0.4       jquerylib_0.1.4  
[21] rmarkdown_2.11    htmlwidgets_1.5.4 munsell_0.5.0     broom_0.7.12     
[25] compiler_4.1.2    httpuv_1.6.5      modelr_0.1.8      xfun_0.29        
[29] pkgconfig_2.0.3   htmltools_0.5.2   tidyselect_1.1.1  workflowr_1.7.0  
[33] fansi_1.0.2       crayon_1.5.0      tzdb_0.2.0        dbplyr_2.1.1     
[37] withr_2.4.3       later_1.3.0       grid_4.1.2        jsonlite_1.7.3   
[41] gtable_0.3.0      lifecycle_1.0.1   DBI_1.1.2         git2r_0.29.0     
[45] magrittr_2.0.2    scales_1.1.1      cli_3.2.0         stringi_1.7.6    
[49] fs_1.5.2          promises_1.2.0.1  xml2_1.3.3        bslib_0.3.1      
[53] ellipsis_0.3.2    generics_0.1.2    vctrs_0.3.8       tools_4.1.2      
[57] glue_1.6.1        crosstalk_1.2.0   hms_1.1.1         fastmap_1.1.0    
[61] yaml_2.3.4        colorspace_2.0-2  rvest_1.0.2       knitr_1.37       
[65] haven_2.4.3       sass_0.4.0