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Welcome to the ExtracellularEnzymeActivity_Data_Prep wiki!

The goal of ExtracellularEnzymeActivity_Data_Prep is to import/clean and explore FLEE lab Extracellular Enzyme Activity (EEA) data from microplate readings. The data from the reader must be saved as .xlsx files, named after the sample as SampleDayNumber_replicate_factor (ex: S09_B_C3 in the sample case represents 9th day sample, replicate B, factor level "C3") within the "data" folder.

library(data.table)
library(readxl)
library(purrr)
library(ggplot2)

You'll still need to render README.Rmd regularly, to keep README.md up-to-date.

Get the file names as sample names and the functions

BiblioDir = list.dirs(path = "data", full.names =T, recursive = F)
paths = list.files(BiblioDir, full.names = T)
source("R/functions.R")
source("R/plotting_functions.R")

Read the enzyme activity data from the plate readings

Gly = enzyme_as_data_table(paths, func=read_glu)
Xyl = enzyme_as_data_table(paths, func=read_xyl)
Cbh = enzyme_as_data_table(paths, func=read_Cbh)

Data is stored as lists for ease of use when the sample number is high

list_data = map(list(Gly=Gly, Xyl=Xyl, Cbh=Cbh), convert_to_numeric)
list_data = map(list_data, calculate_mean)

Calculate each enzyme ratio separately. Check the functions folder for more details

ER_xyl_glu = calculate_xyl_gly (list_data)
ER_glu_xyl_cbh = calculate_glu.xyl_cbh (list_data)

Convert the NaN and Inf values to 0 since these are all below the detection limit values due to the negative data in the measurements.

list = list(ER_xyl_glu, ER_glu_xyl_cbh)
ER_data = Reduce(function (...)  merge(..., by="sample"), list) 

ER_data[is.nan.data.frame(ER_data)] <- 0
ER_data[is.inf.data.frame(ER_data)] <- 0

Cleaning and appropriately naming the factors

ER_data[,c("sample_date", "replicate", "col_no") := tstrsplit(sample, "_")]
ER_data$sample_date = factor(ER_data$sample_date,
                           levels = c("S09", "S13", "S16", "S19"),
                           labels = c("Day0", "Day3", "Day10", "Day17")) #Convert the sample date to days as a factor for ease in plotting
ER_data$col_no = factor(ER_data$col_no,
                                 levels = c("C1", "C2"),
                                 labels = c("Col1", "Col2"))

ER_data = set_coloring_column(ER_data)
ggplot(ER_data, mapping = aes(x=sample_date, y = xyl_gly.median))+
  facet_grid(~col_no, labeller = as_labeller(col_names))+
  geom_boxplot(mapping = aes(fill = highlight, col = highlight))+
  fill_col_no2 () + color_col_no2() +
  theme_boxplot() +
  ylab("Xyl/Glu")