Data loading

suppressPackageStartupMessages({
  library(SummarizedExperiment)
  library(SEtools)
  library(edgeR)
  library(DT)
  library(pheatmap)
  library(plotly)
  library(dplyr)
  library(sva)
  library(lme4)
  library(lmerTest)
  library(readxl)
})
source("Functions/EDC_Functions.R")
source("Functions/CriFormatted.R")
source("Functions/dround.R")

Tadpoles

names(concs) <- concs <- c(paste0(c(1,10,100,1000),"X"),"CTRL vs 1X,10X,100X","CTRL vs 1000X")
e <- bind_rows(lapply(concs, FUN=function(x){
  x <- read_excel("Data/DoseResponse/summary mobility N0 pool_ML.xlsx", sheet=x)
  x$Time <- as.numeric(strptime(x$Time, "%H:%M:%S")-strptime("0:00:00", "%H:%M:%S"))
  x$Light <- rep(rep(factor(c("light","dark")), each=3),nrow(x)/6)
  reshape2::melt(x[,-2], id.vars=c("Time","Light"), variable.name="Tadpole", value.name="Movement")
}), .id="Concentration")
e$Tadpole <- as.factor(e$Tadpole)
e$Batch <- ifelse(grepl("1000",e$Concentration), "2","1")
e$Concentration[grep("CTRL",e$Concentration)] <- "CTRL"
e$Concentration <- relevel(factor(e$Concentration, unique(e$Concentration)), "CTRL")
# sanity check
# ag <- aggregate(x=e$Movement, by=e[,c("Time","Concentration")], FUN=mean)
# ggplot(ag, aes(Time, x, colour=Concentration)) + geom_line()

Mixed linear models

mod <- lmer(Movement~(1|Batch)+(1|Tadpole/Concentration)+Time+Light*Concentration, data=e)
co <- as.data.frame(coef(summary(mod)))[-1:-3,]
co$FDR <- p.adjust(co[,5])
colnames(co)[2] <- "StdErr"
ggplot(cbind(co, coef=row.names(co)), aes(Estimate, coef, colour=-log10(FDR))) + 
  geom_vline(xintercept=0, linetype="dashed") + geom_point(size=3) + 
  geom_segment(aes(x=Estimate-StdErr, xend=Estimate+StdErr, y=coef, yend=coef), size=1.3) +
  geom_text(label=ifelse(co$FDR<0.01,"*",""), size=10, aes(x=Estimate+StdErr+0.025)) +
  labs(x="Change in movement", y="Coefficient")

dround(co[,c(1,2,5,6)])
##                               Estimate StdErr Pr(>|t|)      FDR
## Concentration1X                0.03020 0.0515 5.58e-01 1.00e+00
## Concentration10X              -0.00387 0.0512 9.40e-01 1.00e+00
## Concentration100X              0.05140 0.0508 3.13e-01 1.00e+00
## Concentration1000X             0.02940 0.0571 6.06e-01 1.00e+00
## Lightlight:Concentration1X    -0.10500 0.0226 3.51e-06 1.75e-05
## Lightlight:Concentration10X   -0.16800 0.0224 7.79e-14 4.67e-13
## Lightlight:Concentration100X  -0.20500 0.0222 3.62e-20 2.54e-19
## Lightlight:Concentration1000X -0.40000 0.0250 1.94e-57 1.55e-56
co2 <- co[,c("Estimate","StdErr")]
co2$cycle <- ifelse(grepl("Light",row.names(co2)),"Light","Dark")
co2$Conc2 <- gsub("Concentration","",gsub("Lightlight:","",row.names(co2),fixed=TRUE))
co2 <- rbind(data.frame(Estimate=c(0,0),StdErr=c(0,0),cycle=c("Light","Dark"),Conc2="CTRL"),co2)
co2$Conc2 <- factor(co2$Conc2, unique(co2$Conc2))
ggplot(co2, aes(as.integer(Conc2), Estimate, colour=cycle)) + geom_point() +
  geom_segment(aes(y=Estimate-StdErr,yend=Estimate+StdErr,xend=as.integer(Conc2))) + 
  geom_smooth(method="lm") + scale_x_continuous(breaks=1:5, labels=levels(co2$Conc2)) +
  labs(x="Concentration", y="Change in movement")
## `geom_smooth()` using formula 'y ~ x'

Zebrafish

names(concs) <- concs <- c("CTRL",paste0(c(0.01,0.1,1,10,100),"X"))
e <- bind_rows(lapply(concs, FUN=function(x){
  x <- read_excel("Data/DoseResponse/zebrafish.xlsx", sheet=x)
  x$Time <- as.numeric(gsub(" min","",x$Time))
  x$Light <- rep(rep(factor(c("dark","light"), c("light","dark")), each=5),nrow(x)/10)
  reshape2::melt(x[,-2], id.vars=c("Time","Light"), variable.name="Tadpole", value.name="Movement")
}), .id="Concentration")
e$Tadpole <- as.factor(paste(e$Concentration,e$Tadpole))
e$Concentration <- relevel(factor(e$Concentration, unique(e$Concentration)), "CTRL")
# sanity check
ag <- aggregate(x=e$Movement, by=e[,c("Time","Concentration")], FUN=mean)
ggplot(ag, aes(Time, x, colour=Concentration)) + geom_line() + labs(x="Time (min)", y="Movement")

Mixed linear models

mod <- lmer(Movement~(1|Tadpole)+Time+Light*Concentration, data=e)
co <- as.data.frame(coef(summary(mod)))[-1:-3,]
co$FDR <- p.adjust(co[,5])
colnames(co)[2] <- "StdErr"
co$coef <- factor(row.names(co), unique(row.names(co)))
levels(co$coef) <- gsub("Concentration","",levels(co$coef))
levels(co$coef) <- gsub("Lightdark:","Dark+",levels(co$coef))
ggplot(co, aes(Estimate, coef, colour=-log10(FDR))) + 
  geom_vline(xintercept=0, linetype="dashed") + geom_point(size=3) + 
  geom_segment(aes(x=Estimate-StdErr, xend=Estimate+StdErr, y=coef, yend=coef), size=1.3) +
  geom_text(label=ifelse(co$FDR<0.05,"*",""), size=10, aes(x=Estimate+StdErr+0.025)) +
  labs(x="Change in movement", y="Coefficient")

co1 <- dround(co[,c(7,1,2,5,6)])
row.names(co1) <- NULL
co1
##          coef Estimate StdErr  Pr(>|t|)       FDR
## 1       0.01X  -0.0137 0.0591  8.16e-01  1.00e+00
## 2        0.1X   0.0838 0.0578  1.48e-01  7.39e-01
## 3          1X   0.0402 0.0582  4.90e-01  1.00e+00
## 4         10X   0.0339 0.0574  5.55e-01  1.00e+00
## 5        100X   0.1790 0.0574  1.91e-03  1.34e-02
## 6  Dark+0.01X  -0.0383 0.0275  1.64e-01  7.39e-01
## 7   Dark+0.1X   0.0431 0.0269  1.09e-01  6.52e-01
## 8     Dark+1X   0.0966 0.0271  3.62e-04  2.90e-03
## 9    Dark+10X   0.1350 0.0267  4.46e-07  4.02e-06
## 10  Dark+100X   0.8120 0.0267 1.54e-197 1.54e-196
co2 <- co[,c("Estimate","StdErr")]
co2$cycle <- ifelse(grepl("Light",row.names(co2)),"Light","Dark")
co2$Conc2 <- gsub("Concentration","",gsub("Lightdark:","",row.names(co2),fixed=TRUE))
co2 <- rbind(data.frame(Estimate=c(0,0),StdErr=c(0,0),cycle=c("Light","Dark"),Conc2="CTRL"),co2)
co2$Conc2 <- factor(co2$Conc2, unique(co2$Conc2))
ggplot(co2, aes(as.integer(Conc2), Estimate, colour=cycle)) + 
  geom_hline(yintercept=0, linetype="dashed") + geom_point() +
  geom_segment(aes(y=Estimate-StdErr,yend=Estimate+StdErr,xend=as.integer(Conc2))) + 
  geom_smooth(method="loess", span=1, level=0.9) + 
  scale_x_continuous(breaks=1:6, labels=levels(co2$Conc2)) +
  labs(x="Concentration", y="Change in movement")
## `geom_smooth()` using formula 'y ~ x'

Authors

Nicolò Caporale: ,

Cristina Cheroni:

Pierre-Luc Germain:

Giuseppe Testa:

Lab: http://www.testalab.eu/

‘Date: December 01, 2021’

sessionInfo()
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur 10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/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] parallel  stats4    stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] readxl_1.3.1                lmerTest_3.1-3             
##  [3] lme4_1.1-26                 Matrix_1.3-2               
##  [5] sva_3.38.0                  BiocParallel_1.24.1        
##  [7] genefilter_1.72.1           mgcv_1.8-34                
##  [9] nlme_3.1-152                dplyr_1.0.5                
## [11] plotly_4.9.3                ggplot2_3.3.3              
## [13] pheatmap_1.0.12             DT_0.17                    
## [15] edgeR_3.32.1                limma_3.46.0               
## [17] SEtools_1.4.0               SummarizedExperiment_1.20.0
## [19] Biobase_2.50.0              GenomicRanges_1.42.0       
## [21] GenomeInfoDb_1.26.2         IRanges_2.24.1             
## [23] S4Vectors_0.28.1            BiocGenerics_0.36.0        
## [25] MatrixGenerics_1.2.1        matrixStats_0.58.0         
## 
## loaded via a namespace (and not attached):
##   [1] minqa_1.2.4            Rtsne_0.15             colorspace_2.0-0      
##   [4] rjson_0.2.20           ellipsis_0.3.1         circlize_0.4.12       
##   [7] XVector_0.30.0         GlobalOptions_0.1.2    clue_0.3-58           
##  [10] farver_2.1.0           bit64_4.0.5            AnnotationDbi_1.52.0  
##  [13] fansi_0.4.2            codetools_0.2-18       splines_4.0.3         
##  [16] cachem_1.0.4           knitr_1.31             jsonlite_1.7.2        
##  [19] nloptr_1.2.2.2         Cairo_1.5-12.2         annotate_1.68.0       
##  [22] cluster_2.1.1          png_0.1-7              compiler_4.0.3        
##  [25] httr_1.4.2             assertthat_0.2.1       fastmap_1.1.0         
##  [28] lazyeval_0.2.2         htmltools_0.5.1.1      tools_4.0.3           
##  [31] gtable_0.3.0           glue_1.4.2             GenomeInfoDbData_1.2.4
##  [34] reshape2_1.4.4         V8_3.4.0               Rcpp_1.0.6            
##  [37] cellranger_1.1.0       jquerylib_0.1.3        vctrs_0.3.7           
##  [40] iterators_1.0.13       xfun_0.21              stringr_1.4.0         
##  [43] openxlsx_4.2.3         lifecycle_1.0.0        statmod_1.4.35        
##  [46] XML_3.99-0.5           MASS_7.3-53.1          zlibbioc_1.36.0       
##  [49] scales_1.1.1           TSP_1.1-10             RColorBrewer_1.1-2    
##  [52] ComplexHeatmap_2.6.2   yaml_2.2.1             curl_4.3              
##  [55] memoise_2.0.0          sass_0.3.1             stringi_1.5.3         
##  [58] RSQLite_2.2.3          highr_0.8              randomcoloR_1.1.0.1   
##  [61] foreach_1.5.1          seriation_1.2-9        boot_1.3-27           
##  [64] zip_2.1.1              shape_1.4.5            rlang_0.4.10          
##  [67] pkgconfig_2.0.3        bitops_1.0-6           evaluate_0.14         
##  [70] lattice_0.20-41        purrr_0.3.4            labeling_0.4.2        
##  [73] htmlwidgets_1.5.3      bit_4.0.4              tidyselect_1.1.0      
##  [76] plyr_1.8.6             magrittr_2.0.1         R6_2.5.0              
##  [79] generics_0.1.0         DelayedArray_0.16.1    DBI_1.1.1             
##  [82] pillar_1.5.1           withr_2.4.1            survival_3.2-7        
##  [85] RCurl_1.98-1.2         tibble_3.1.0           crayon_1.4.1          
##  [88] utf8_1.2.1             rmarkdown_2.7          GetoptLong_1.0.5      
##  [91] locfit_1.5-9.4         grid_4.0.3             data.table_1.14.0     
##  [94] blob_1.2.1             digest_0.6.27          xtable_1.8-4          
##  [97] numDeriv_2016.8-1.1    tidyr_1.1.3            munsell_0.5.0         
## [100] registry_0.5-1         viridisLite_0.3.0      bslib_0.2.4