BrothCode

#Code for broth microdilution plates in differnt media

#packages; just hit enter
{library (gplots)
  library (plyr)  
  library (lattice) 
  library (Rmisc) 
  library (car) 
  library (FSA) 
  library (multcompView) 
  library (multcomp) 
  library (agricolae) 
  library (DescTools)
  library (rcompanion)
  library (ggplot2)
  library(ggsignif)
  library(reshape2)
  library(tidyverse)
  library(ggthemes)
  library(ggprism)
  }

Dataset = DATATITLE
attach(Dataset)
names(Dataset)
{
DMEM = "hotpink"
RPMI = "salmon"
YPD = "burlywood"
}
 

#Edit the antifungal and concentration; only edit if necessary, not usually needed
AF = "Amphotericin B" 
Conc = 1 # remember this is 1/2 of the calculation since diluting 2 fold
{AFlabel = paste(AF, "Concentration (ug/mL)", sep=" ")
  numberlist = round(Conc/2^(seq(0, 9, by = 1)),3)
  numberlist = c(numberlist ,"Untreated", "No Cells")
  NDnumberlist = c("Untreated", "No Cells")

}


#Datalabels
{ODXTT = expression(OD[495*"nm"])
  ODCV = expression(OD[595*"nm"])
  OD600 = expression(OD[600*"nm"])
  AbsXTT = expression(Absorbance[495*"nm"])
  AbsCV = expression(Absorbance[595*"nm"])
  Abs600 = expression(Absorbance[600*"nm"])
  }

#Generate data to produce table
Data = summarySE(data = Dataset, "Absorbance", group = "Column", conf.interval = 0.95)


Plot  = ggplot(Data,
               aes(x = Column, y = Absorbance, ymax = 30, ymin = 0 )) +
  geom_bar(stat = "identity", fill = DMEM, col = "black", width = 0.7) +
  geom_errorbar(aes(ymin = Absorbance - se, ymax = Absorbance + se),
                width = 0.2, 
                size = 0.5)  +
  geom_point(data = Dataset,
             aes(),alpha = 0.3, size = 4, shape = 17) +
  scale_shape_manual(values = 18 ) +
  scale_y_continuous(name = ODCV,
                     breaks = seq(0,500,by = 10)) +
  scale_x_discrete(name = AFlabel,
                   breaks = Data$Column,
                   labels= numberlist) +
  scale_color_prism("floral") + 
  theme_prism(base_size = 16,
              axis_text_angle = 45) +
scale_fill_prism("floral") 
  guides(y = "prism_offset_minor") 
Plot

grid.arrange(test1, test2, ncol = 1, nrow = 2)