So you analyzed your mass spectrometry raw files and want to some post-processing steps. Look no further. This script will generate QC plots and volcano plots highlighting your proteins of interest.
Getting started is easy. Download the R script and analysis parameters file to your working directory. To do this:
- Click on the big green button in the top right that says
<> Codeand then click onDownload ZIP. - Place the files in your working directory
- Fill in the analysis parameter file accordingly.
- Open the R script with RStudio, select all and run it.
Note: - Installing the DEP package for the first time may take a while. Should be smooth sailing after that
Explanations are also present in the Excel file, when hovering over the parameter boxes.
analysis_method - One of "DiaNN", "MaxQuant" or "Proteome discoverer".
conditions - The amount of experimental variables. This can be either 2 (Condition A, Replicates) or 3 (Condition B, Condition A, Replicates). These variables should be present in the .raw file names.
filtering_type - Whether a protein should have a value in all samples ("complete") or all samples in at least one condition/group ("condition").
mass_spec - This should be present in the names of the .raw files. Required when selecting DiaNN as analysis method.
comparison - The type of comparison that will be tested. This can be all possible pairwise comparisons ("all") or limited to the comparisons versus the control ("control").
control - In case you choose "control" as your comparison, add the name of the control sample, e.g. DMSO, IgG, untreated, KO.
unique_peptides - The minimum amount of unique peptides a protein should be quantified with.
volcano - Specifiy which proteins to highlight in the volcano plot. Can be either a list of supplied protein names ("protein list"), all proteins above a supplied p-value and fold change cutoff ("specify significance") or the top N most differential proteins below a set p-value ("TopN").
proteins_to_highlight - list of protein names to be highlighted, separated by a semicolon (;).
p_value - p-value cutoff for significance. REQUIRED
log2_FC - log2 FC value cutoff for significance. REQUIRED
TopN - TopN number of proteins to highlight.
complete_output - If set to TRUE, the 'DEP_results' output file will contain a tab titled 'complete_output' containing the raw, normalized and imputated LFQ values for each sample, as well as all columns from the dep results object.
Make sure your .raw files and output are correctly named, as outlined below. Otherwise the script may not run succesfully.
.raw mass spec files - Please ensure that the abundance column names (and thus the .raw files) contain the name of the mass spectrometer used (e.g. Astral, Exploris) and the following information, in order and separated by an underscore:
- Condition A (e.g. Cell line)
- Condition B (e.g. WT and KO or treated and untreated)
- Replicate
Example: 20250205_Astral_AUR_DZ114_Wildtype_untreated_1.raw
DiaNN - Output files should end on *pg_matrix.tsv and *pr_matrix.tsv.
MaxQuant - Output file should end on *proteinGroups.txt and the experiment name should follow a similar format as the .raw mass spec files, as specified above.
Proteome Discoverer - Output file should end on *proteins.txt and the experiment name should follow a similar format as the .raw mass spec files, as specified above.
This script uses a lot of the DEP package, so credit to them for developing the package (Zhang X, Smits A, van Tilburg G, Ovaa H, Huber W, Vermeulen M (2018). “Proteome-wide identification of ubiquitin interactions using UbIA-MS.” Nature Protocols, 13, 530–550).