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Compid – A New Software Tool to Integrate and Compare MS/MS Based Protein Identification Results from Mascot and Paragon

Niina Lietzén, Lari Natri, Olli Nevalainen, Jussi Salmi, Tuula Nyman, Compid – A New Software Tool to Integrate and Compare MS/MS Based Protein Identification Results from Mascot and Paragon. Journal of Proteome Research , 2010.

Abstract:

Tandem mass spectrometry-based proteomics experiments produce large amounts of raw data, and different database search engines are needed to reliably identify all the proteins from this data. Here, we present Compid, an easy-to-use software tool that can be used to integrate and compare protein identification results from two search engines, Mascot and Paragon. Additionally, Compid enables extraction of information from large Mascot result files that cannot be opened via the Web interface and calculation of general statistical information about peptide and protein identifications in a data set. To demonstrate the usefulness of this tool, we used Compid to compare Mascot and Paragon database search results for mitochondrial proteome sample of human keratinocytes. The reports generated by Compid can be exported and opened as Excel documents or as text files using configurable delimiters, allowing the analysis and further processing of Compid output with a multitude of programs. Compid is freely available and can be downloaded from http://users.utu.fi/lanatr/compid . It is released under an open source license (GPL), enabling modification of the source code. Its modular architecture allows for creation of supplementary software components e.g. to enable support for additional input formats and report categories.

BibTeX entry:

@ARTICLE{jLiNaNeSaNy10a,
  title = {Compid – A New Software Tool to Integrate and Compare MS/MS Based Protein Identification Results from Mascot and Paragon},
  author = {Lietzén, Niina and Natri, Lari and Nevalainen, Olli and Salmi, Jussi and Nyman, Tuula},
  journal = {Journal of Proteome Research},
  year = {2010},
  keywords = {protemics, mass spectrometry, algorithmics},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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