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Binder

ASMS_2024_DIA

All the files for analysis are prepared from the raw files. Only if you want to follow the analysis from the start to the end first download the following files (repository: pride/PXD028735):

  • LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_01.raw
  • LFQ_Orbitrap_DDA_Condition_B_Sample_Alpha_01.raw
  • LFQ_Orbitrap_AIF_Human_01.raw
  • LFQ_Orbitrap_DDA_Human_01.raw
  • LFQ_timsTOFPro_diaPASEF_Human_01.d
  • LFQ_timsTOFPro_PASEF_Human_01.d
  • LFQ_TTOF6600_SWATH_Human_01.wiff.scan
  • LFQ_TTOF6600_SWATH_Human_01.wiff
  • LFQ_TTOF6600_DDA_Human_01.wiff.scan
  • LFQ_TTOF6600_DDA_Human_01.wiff

Conver the files to mzml using MSConvert with vendor peak picking and put them in the mzml file folder. For the timsTOF files please use tdf2mzml.

Analysis

The following section will explain per notebook or python script what analysis is done and what the resulting figures are.

mzml_pdiff_aa.py

Calculate delta m/z distances for all the MS2 spectra. This is later used to quantify potential ambiguity in DDA VS DIA.

diann_searches_mods.ipynb

Do a comparison of different DIA-NN searches and the peptidoforms it identified. The variable modifications are changed between the searches.

FragmentCollision.ipynb

Calculate possible isobaric overlapping amino acid and modification combinations for fragment peaks.

read_speclib_diann.ipynb

Read the spectral library from DIA-NN to spot potential differences for different peptidoforms.

search_spacesize.ipynb

Calculate the search space size based on set parameters and fasta.

visualize_aa_diff.ipynb

Visualize the delta mz values that correspond to amino acids and modifications.

visualize_ms1.ipynb

Visualize the number of MS1 peaks in DDA and DIA data.

visualize_ms2.ipynb

Visualize the number of MS2 peaks in DDA and DIA data.

histone_analysis/spectral_library_calc.ipynb

Compare predictions from DIA-NN to observed histone peptide fragment intensity spectra.