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ppmfixer

A script for pGlyco3 to correct near-isobaric mismatches.

https://github.com/trvadams/ppmfixer

Science Score: 57.0%

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Repository

A script for pGlyco3 to correct near-isobaric mismatches.

Basic Info
  • Host: GitHub
  • Owner: trvadams
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 28.3 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

ppmFixer

This script takes a pGlyco3.0 output file (e.g. pGlycoDB-GP-FDR-Pro-Quant-Site.txt) and outputs a separate .txt file that adds additional columns with corrected N-glycan compositions (not linkages).

Usage:

python ppmFixer <input_file> <output_file>

Example: python ppmFixer.py pGlycoDB-GP-FDR-Pro-Quant-Site.txt output.txt

Required packages: - numpy - pandas

To install the required packages, I recommend the use of miniconda: https://docs.conda.io/projects/miniconda/en/latest/

Once miniconda is installed and activated, use the following commands to install the required packages: conda install numpy conda install pandas For more information please see associated publication: https://doi.org/10.1093/glycob/cwae006

FOR WINDOWS USERS: Using Python on a Windows machine can be a little tricky, so here are additional instructions for Windows users who might be having trouble installing the proper packages.

  1. Download and install Python 3.x (latest version) from here: https://www.python.org/downloads/
  2. Download and install miniconda from here: https://docs.conda.io/projects/miniconda/en/latest/index.html
  3. Open the newly installed Anaconda Powershell Prompt (Miniconda3).
  4. Install the numpy and pandas packages via the powershell. To do this, simply enter: conda install numpy conda install pandas
  5. Use the powershell to run the script. The usage goes: python ppmFixer.py <input_file> <output_file> with your input file being the "pGlycoDB-GP-FDR-Pro-Quant-Site.txt” output from pGlyco, and the output file being whatever you want (e.g. output.txt). Note: If you’re unfamiliar with navigating directories in powershell (which uses a bash-like interface), this link has some tips. https://www.sharepointdiary.com/2021/04/change-directory-in-powershell.html

Owner

  • Name: Trevor
  • Login: trvadams
  • Kind: user
  • Location: Athens, GA

Biochemistry PhD candidate at the University of Georgia - Complex Carbohydrate Research Center - Wells Lab

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: ppmFixer
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Trevor
    family-names: Adams
    email: trevadams94@gmail.com
    affiliation: University of Georgia
    orcid: 'https://orcid.org/0000-0002-6661-1694'
  - given-names: Peng
    family-names: Zhao
    affiliation: University of Georgia
  - given-names: Rui
    family-names: Kong
    affiliation: Emory University
  - given-names: Lance
    family-names: Wells
    affiliation: University of Georgia
    email: lwells@ccrc.uga.edu
identifiers:
  - type: doi
    value: 10.1093/glycob/cwae006
    description: Original publication
repository-code: 'https://github.com/trvadams/ppmFixer'
abstract: >-
  Modern glycoproteomics experiments require the use of
  search engines due to the generation of countless spectra.
  While these tools are valuable, manual validation of
  search engine results is often required for detailed
  analysis of glycopeptides as false-discovery rates are
  often not reliable for glycopeptide data. Near-isobaric
  mismatches are a common source of misidentifications for
  the popular glycopeptide-focused search engine pGlyco3.0,
  and in this technical note we share a strategy and script
  that improves the accuracy of the search utilizing two
  manually validated datasets of the glycoproteins CD16a and
  HIV-1 Env as proof-of-principle.
keywords:
  - glycoproteomics
  - mass spectrometry
license: MIT

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