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Python and R scripts to generate the figures in the MSFragger-DDA+ paper

  • notebook/figure2.ipynb is used to generate Figure 2
  • notebook/figure3.ipynb is used to generate Figure 3
  • notebook/figure4_part1.ipynb is used to generate Figure 4a and 4b
  • notebook/figure4_part2.ipynb is used to generate Figure 4c and 4d
  • notebook/figure4_part3.ipynb is used to generate Figure 4e and 4f
  • notebook/figure5.ipynb and figure5.R is used to generate Figure 5
  • peptide_entrapment.py is used to calculate the peptide-level metrics for the entrapment database search
  • protein_entrapment.py is used to calculate the protein-level metrics for the entrapment database search

Publication

Yu, F., Deng, Y., & Nesvizhskii, A.I. (2024). MSFragger-DDA+ Enhances Peptide Identification Sensitivity with Full Isolation Window Search. bioRxiv, 2024-10.