Load the packages to make the function available

library(MACSQuantifyR)
library(knitr)
library(grid)
library(gridExtra)
library(png)
suppressMessages(library(R.utils))

This is an example file loaded with the package:

file <- system.file("extdata", "drugs.xlsx",
    package = "MACSQuantifyR")

## [1] "drugs.xlsx"

This is what the beginning of the file looks like:

Run the function

This line will generate a plot on which the user has to manually select the replicates.

Once the replicates of all conditions have been identified by the user, the on_plate_selection function will automatically reorder the data and process them.

In the following example, the user is screening for the effect of two drugs on human cell lines at different concentrations.

Each of the 8 conditions contain 3 replicates. (number_of_replicates = 3, number_of_conditions = 8)

(i.e: Drug1_c1 is the concentration for drug1 at concentration c1 and the replicates are B2, C2 ,D2).

One can specify control=T if a control condition needs to be processed.

MACSQuant <- pipeline(filepath = file,
    sheet_name = NULL, # optional
    number_of_replicates = 3,
    number_of_conditions = 8,
    control = T)

The user is notified as the function goes along its tasks.

## ...To quit press ESC...
##  ...You can now select your conditions replicates (without control condition replicates)...
##      --> 18 conditions:...1...2...3...4...5...6...7...8...OK
##      --> Done: replicates identified
##      --> Done: statistics on each condition replicates
##  ...You can now select your control replicates...
##      --> 1 control: ...OK...
##      --> Done: statistics on each control replicates
##  --> Done: replicates stored in variable my_replicates_sorted

The user may encounter warnings:

## Warning: In order_data(sorted_matrix_final, my_data, save.files = save.files) : 
##  !!! A2 not selected and will be ignored

This warning tells the user that there were some conditions that were not selected. Here A2 stands for the calibration well and should not be used in this analysis.

Access the results

The function will create a folder called outputMQ in your current directory and save:

• The well plate template image (plate_template.png)
• The sorted_replicates data table (sorted_table.txt)
• The statistic table (statistics.txt)

Be careful to avoid overriding data, content of existing outputMQ folder could be erased.

The results presented below can be found in the generated report file (results.docx)

• You can find an example of the report generated by the function pipeline() at this address: https://github.com/Peyronlab/MACSQuantifyR