Protein citrullination (or deimination) is an irreversible post-translational modification implicated in several physiological and pathological processes, including gene expression regulation, apoptosis, Rheumatoid arthritis, and Alzheimer's disease. However, challenges in sample preparation and data analysis make it difficult to confidently identify and validate Citrullinated proteins (also known as Citrullinome) and its sites. To overcome these limitations, we generated an algorithm called ‘CitFinder’ to analyze mass spectrometry based spectral libraries to confidently identify and validate citrullinated sites.
- python2.7
- Numpy
git clone https://github.com/Citrullinome/CitFinder.git
Usage: -i -o -f -m -g -s -r Use –h or --help for detailed help for parameter
There are 7 input parameters for CitFinder.py
commond line input | description |
---|---|
-i, --in | SpectraST non_consensus_library.splib in txt format |
-o, --out | Output file of modified peptides pairs with RT information, neutral loss and skyline validation results in csv format |
-f, --fasta | Fasta file required for modification site and 10 amino acid information |
-m, --modification | Please specify one targed mod at a time. For example: R[157] OR R |
-g, --grouping | (Optional) Specify the grouping information and comma seprate them. For example: Heart,Lung,Liver,Muscle,Kidney,Brain. Default will be no grouping |
-s, --skyline | (Optional) Skyline report for validation. Note: the file name and modification mass should be consistent with splib |
-r, --rtShift | (Optional) If rt shift is True, it will only provide the modifed peptide pairs with >= 5 mins rt shift.Otherwise, it will provide all the modified peptide pairs. Default: True |
-
Step1: prepare your input files:
Cit_Mouse_Organs_SpecLib.splib
: Splib file generated from spectrast toolCit_Mouse_Organs_SpecLib_Skyline.csv
: Skyline reports for validation
-
Step2: identification of citrullinated sites:
python CitFinder.py -i Cit_Mouse_Organs_SpecLib.splib -o Cit_Mouse_Organs_SpecLib_CitFinder.csv -g Heart,Lung,Liver,Muscle,Kidney,Brain -f UP_Mouse_Rev_Canonical_20180228_DECOY_iRT.fasta -m R[157]
Upon completion, Cit_Mouse_Organs_SpecLib_CitFinder.csv
will contain the modified peptides pairs with RT and neutral loss information
- Step3: validation of citrullinated sites
python CitFinder.py -i Cit_Mouse_Organs_SpecLib.splib -o Cit_Mouse_Organs_SpecLib_Skyline_CitFinder.csv -g Heart,Lung,Liver,Muscle,Kidney,Brain -f UP_Mouse_Rev_Canonical_20180228_DECOY_iRT.fasta -m R[157] -s Cit_Mouse_Organs_SpecLib_Skyline.csv
Upon completion, Cit_Mouse_Organs_SpecLib_Skyline_CitFinder.csv
will contain the modified peptides pairs with RT and neutral loss information along with skyline validation results.
All inputs and outputs are placed in the Example folder. Manual skyline validation spectrums Skyline_Manual_Validation_Spectrum.pdf
is also placed in the folder for the purposes of comparison.
If you have any questions about CitFinder, please contact Justyna Fert-Bober ([email protected]) or Vidya Venkatraman ([email protected])
Justyna Fert-Bober, Vidya Venkatraman, Christie Hunter, Ruining Liu, Erin L. Crowgey, Rakhi Pandey, Ronald Holewinski, Alexander Scotland, Ben Berman, Jennifer E. Van Eyk, “Enriched Ion Library for Mouse Citrullinome across multiple organ systems”, Manuscript Submitted (2019)
See the LICENSE file for license rights and limitations (Apache2.0).