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R package for the analysis of Multiplex Substrate Profiling by Mass Spectrometry for Proteases (MSP-MS) Data

License: Other

R 100.00%
protease proteomics proteomics-data-analysis

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mspms's Issues

automated report

add a function to generate an automated .Rmd report going over the results of the experiment.

plot_heatmap

the cleavage annotations in the heatmap do not match the peptide. Need to investigate and fix.

real sequence vs match sequence

Think about what to do about this. Should I alter it ? Or just leave it?

Briefly, it is the way it is because methionines in the peptide library were replaced with norleucines (which have the same side chain as methionine with the S converted to C but are the same exact mass as L). This was done because methionines can be oxidized either singly or doubly which could pose problems, but n should be similar to M in the way it is recognized by proteases.

Peaks recognizes n as L, and then we change it to a M in the code because that is all IceLogo can handle. Then we know that the M is actually a n, and change it later in illustrator.

N from cleavage event

Currently, the package only reports the 4 AA to the left and right of the cleavage event. It would be beneficial to make this a user-specified variable that defaults to 4

PTM support

I think that if PTMs are included in the search, it will mess up the current logic. Might need to fix this.

Full length peptides

Full-length peptides don't appear to be included in the heatmap of data. Check to see what is happening here.

motif analysis

Check to see if there is some sort of open-source R solution to doing an IceLogo-like motif analysis.

It would be beneficial to make this work off of quantified values. Currently, the method just does some sort of enrichment analysis based on the motifs it was detected in compared to the background.

support for other upstream MS processing software

It would be good to add support for other MS processing software. If we added support for the following that would pretty much cover it.

  1. PEAKS
  2. Proteome discoverer
  3. Fragpipe
  4. Spectronaut

We could implement this by doing something similar to how MSStats has functions to convert files into a standardized input that is then subsequently processed.

mspms function

add function that wraps all parts of the workflow into one function. Thinking it could be simply called mspms.

volcano plot ordering

change levels of factors to make t_test comparisons order by time. Relatedly, add a dedicated plot_volcano function

quality score differences

There are differences in the quality metrics used by proteome discoverer and PEAKS. Take a look into this.

QC metrics

Add QC metrics

  • How many full-length peptides from the library are detected at T0? (should be at least ~200 out of the 228)

  • How many of the library peptides are found including all cleavages?

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