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.