Calculates fragment intensities and doublet intensities of cross-linked peptides from MS Annika CSMs.
- Install requirements:
pip install -r requirements.txt - Export MS Annika CSMs from Proteome Discoverer to Microsoft Excel format. Filter out decoys beforehand. Optionally also filter out low confidence CSMs.
- [Optional] Export MS Annika Crosslink Doublets to text (tab seperated) if you want to annotate doublet peaks.
- Convert any RAW files to *.mgf format.
- Set your desired parameters in
get_intensities.py. - Run
python get_intensities.py. - If the script successfully finishes, there should be a new Excel file including intensities and annotations.
The following parameters should be set inside the script:
##### PARAMETERS #####
SPECTRA_FILE = "20220215_Eclipse_LC6_PepMap50cm-cartridge_mainlib_DSSO_3CV_stepHCD_OT_001.mgf"
CSMS_FILE = "CSMs_unfiltered.xlsx"
DOUBLETS_FILE = "CrosslinkDoublets.txt"
MODIFICATIONS = \
{"Oxidation": [15.994915],
"Carbamidomethyl": [57.021464],
"DSSO": [54.01056, 85.98264, 103.99320]}
ION_TYPES = ("b", "y")
MAX_CHARGE = 4
MATCH_TOLERANCE = 0.02
DOUBLET_IDENTIFICATION_MODE = "All"
# DOUBLET_IDENTIFICATION_MODE = "Evidence"
# DOUBLET_IDENTIFICATION_MODE = "Indication"
######################The DOUBLETS_FILE parameter is optional, if a file is provided the doublet intensities will also be calculated, otherwise leave the field blank DOUBLETS_FILE = None and doublets will not be annotated and no doublet intensities will be calculated. DOUBLET_IDENTIFICATION_MODE can either be "All" which means all doublets will be considered or "Evidence" which means only doublets identified by MS Annika in evidence mode will be considered, or "Indication" which means only doublets identified by MS Annika in indication mode will be considered.
If you are using the MS Annika CSM Annotation script please cite:
MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity
Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer
Journal of Proteome Research 2023 22 (9), 3009-3021
DOI: 10.1021/acs.jproteome.3c00325
If you are using MS Annika please cite as described here.