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IdentiPy: An Extensible Search Engine for Protein Identification in Shotgun Proteomics.

Lev I LevitskyMark V IvanovAnna A LobasJulia A BubisIrina A TarasovaElizaveta M SolovyevaMarina L PridatchenkoMikhail V Gorshkov
Published in: Journal of proteome research (2018)
We present an open-source, extensible search engine for shotgun proteomics. Implemented in Python programming language, IdentiPy shows competitive processing speed and sensitivity compared with the state-of-the-art search engines. It is equipped with a user-friendly web interface, IdentiPy Server, enabling the use of a single server installation accessed from multiple workstations. Using a simplified version of X!Tandem scoring algorithm and its novel "autotune" feature, IdentiPy outperforms the popular alternatives on high-resolution data sets. Autotune adjusts the search parameters for the particular data set, resulting in improved search efficiency and simplifying the user experience. IdentiPy with the autotune feature shows higher sensitivity compared with the evaluated search engines. IdentiPy Server has built-in postprocessing and protein inference procedures and provides graphic visualization of the statistical properties of the data set and the search results. It is open-source and can be freely extended to use third-party scoring functions or processing algorithms and allows customization of the search workflow for specialized applications.
Keyphrases
  • machine learning
  • electronic health record
  • high resolution
  • deep learning
  • mass spectrometry
  • big data
  • autism spectrum disorder
  • small molecule
  • data analysis
  • tandem mass spectrometry