examine_Tarantino_OFT

Read in Data

library(data.table)
library(stats)
library(knitr)

## Warning: package 'knitr' was built under R version 3.1.2

opts_chunk$set(comment = NA, results = "asis", comment = NA, tidy = F)

Tarantino1 <- readRDS('Tarantino_day1_phenotypes_raw.RDS')

boxplot of all strains in three different scales

par(las = 2)
boxplot(formula = TotDst ~ Strain, data = Tarantino1)

t.none <- Tarantino1[, list(mean = mean(TotDst, na.rm = TRUE),
                            var = var(TotDst, na.rm = TRUE)),
                     by = Strain]
rank(t.none$mean)[8]

[1] 1

rank(t.none$var)[8]

[1] 7

boxplot(formula = sqrt(TotDst) ~ Strain, data = Tarantino1)

t.sqrt <- Tarantino1[, list(mean = mean(sqrt(TotDst), na.rm = TRUE),
                            var = var(sqrt(TotDst), na.rm = TRUE)),
                     by = Strain]
rank(t.sqrt$mean)[8]

[1] 1

rank(t.sqrt$var)[8]

[1] 40

boxplot(formula = log(TotDst) ~ Strain, data = Tarantino1)

t.nlog <- Tarantino1[, list(mean = mean(log(TotDst), na.rm = TRUE),
                            var = var(log(TotDst), na.rm = TRUE)),
                     by = Strain]
rank(t.nlog$mean)[8]

[1] 1

rank(t.nlog$var)[8]

[1] 45

mean-variance plot of all strains in three different scales

library(rCharts)

none.plot <- rPlot(var ~ mean, data = t.none, type = 'point', color = 'Strain')
none.plot$guides( 
  x = list( 
    min = pretty( t.none$mean ) [1],
    max = tail( pretty( t.none$mean ), 1 ),
    numticks = length( pretty( t.none$mean ) ),
    labels = pretty( t.none$mean )
    ),
  y = list( 
    min = pretty( t.none$var ) [1],
    max = tail( pretty( t.none$var ), 1 ),
    numticks = length( pretty( t.none$var ) ),
    labels = pretty( t.none$var )
    )
  )
none.plot$print('rplot1', include_assets = TRUE)

sqrt.plot <- rPlot(var ~ mean, data = t.sqrt, type = 'point', color = 'Strain')
sqrt.plot$guides( 
  x = list( 
    min = pretty( t.sqrt$mean ) [1],
    max = tail( pretty( t.sqrt$mean ), 1 ),
    numticks = length( pretty( t.sqrt$mean ) ),
    labels = pretty( t.sqrt$mean )
    ),
  y = list( 
    min = pretty( t.sqrt$var ) [1],
    max = tail( pretty( t.sqrt$var ), 1 ),
    numticks = length( pretty( t.sqrt$var ) ),
    labels = pretty( t.sqrt$var )
    )
  )
sqrt.plot$print('rplot2', include_assets = TRUE)

nlog.plot <- rPlot(var ~ mean, data = t.nlog, type = 'point', color = 'Strain')
nlog.plot$guides( 
  x = list( 
    min = pretty( t.nlog$mean ) [1],
    max = tail( pretty( t.nlog$mean ), 1 ),
    numticks = length( pretty( t.nlog$mean ) ),
    labels = pretty( t.nlog$mean )
    ),
  y = list( 
    min = pretty( t.nlog$var ) [1],
    max = tail( pretty( t.nlog$var ), 1 ),
    numticks = length( pretty( t.nlog$var ) ),
    labels = pretty( t.nlog$var )
    )
  )
nlog.plot$print('rplot3', include_assets = TRUE)